Welling, M.[Max],
Weber, M.[Markus],
Positive tensor factorization,
PRL(22), No. 12, October 2001, pp. 1255-1261.
Elsevier DOI
0108
BibRef
Sun, Z.H.[Zhao-Hui],
Ramesh, V.[Visvanathan],
Tekalp, A.M.[A. Murat],
Error Characterization of the Factorization Method,
CVIU(82), No. 2, May 2001, pp. 110-137.
DOI Link
0108
BibRef
Anandan, P.,
Irani, M.[Michal],
Factorization with Uncertainty,
IJCV(49), No. 2-3, September-October 2002, pp. 101-116.
DOI Link
0209
BibRef
Earlier: A2, A1:
ECCV00(I: 539-553).
Springer DOI
0003
Award, ECCV.
BibRef
Zelnik-Manor, L.[Lihi],
Irani, M.[Michal],
On Single-Sequence and Multi-Sequence Factorizations,
IJCV(67), No. 3, May 2006, pp. 313-326.
Springer DOI
0606
BibRef
Earlier:
Temporal Factorization vs. Spatial Factorization,
ECCV04(Vol II: 434-445).
Springer DOI
0405
Rather than grouping the same motions, group the same shapes.
Thus get the same expressions even if the head moves.
See also Multi-body Factorization with Uncertainty: Revisiting Motion Consistency.
BibRef
Fanti, C.[Claudio],
Zelnik-Manor, L.[Lihi],
Perona, P.[Pietro],
Hybrid Models for Human Motion Recognition,
CVPR05(I: 1166-1173).
IEEE DOI
0507
BibRef
Zelnik-Manor, L.[Lihi],
Machline, M.[Moshe],
Irani, M.[Michal],
Multi-body Factorization with Uncertainty:
Revisiting Motion Consistency,
IJCV(68), No. 1, June 2006, pp. 27-41.
Springer DOI
0605
Into regions of consistent motion.
Temporal consistency of actions across multiple frames.
BibRef
Aanĉs, H.[Henrik],
Fisker, R.[Rune],
Ċström, K.[Kalle],
Carstensen, J.M.[Jens Michael],
Robust Factorization,
PAMI(24), No. 9, September 2002, pp. 1215-1225.
IEEE Abstract.
0209
How to deal with it when there is not a set of tracked features.
Modification of the Christy-Horaud (
See also Euclidean Shape and Motion from Multiple Perspective Views by Affine Iterations. )
scheme.
BibRef
Fiore, P.D.,
A constant modulus matrix factorization for direction finding and array
calibration,
SPLetters(9), No. 9, September 2002, pp. 272-274.
IEEE Top Reference.
0211
BibRef
Wild, S.[Stefan],
Curry, J.[James],
Dougherty, A.[Anne],
Improving non-negative matrix factorizations through structured
initialization,
PR(37), No. 11, November 2004, pp. 2217-2232.
Elsevier DOI
0409
BibRef
Klingenberg, B.[Bradley],
Curry, J.[James],
Dougherty, A.[Anne],
Non-negative matrix factorization: Ill-posedness and a geometric
algorithm,
PR(42), No. 5, May 2009, pp. 918-928.
Elsevier DOI
0902
Non-negative matrix factorization, Geometry, Ill-posedness, Generative
model, Component analysis
BibRef
Corinthios, M.J.,
Generalised transform factorisation for massive parallelism,
VISP(151), No. 3, June 2004, pp. 153-163.
IEEE Abstract.
0409
BibRef
Pascual-Montano, A.[Alberto],
Carazo, J.M.,
Kochi, K.[Kieko],
Lehmann, D.[Dietrich],
Pascual-Marqui, R.D.[Roberto D.],
Nonsmooth Nonnegative Matrix Factorization (nsNMF),
PAMI(28), No. 3, March 2006, pp. 403-415.
IEEE DOI
0602
optimization of an unambiguous cost function designed to explicitly
represent sparseness.
BibRef
Okatani, T.[Takayuki],
Deguchi, K.[Koichiro],
On the Wiberg Algorithm for Matrix Factorization in the Presence of
Missing Components,
IJCV(72), No. 3, May 2007, pp. 329-337.
Springer DOI
0702
BibRef
Okatani, T.[Takayuki],
Yoshida, T.[Takahiro],
Deguchi, K.[Koichiro],
Efficient algorithm for low-rank matrix factorization with missing
components and performance comparison of latest algorithms,
ICCV11(842-849).
IEEE DOI
1201
BibRef
Kanatani, K.[Kenichi],
Sugaya, Y.[Yasuyuki],
Ackermann, H.[Hanno],
Uncalibrated Factorization Using a Variable Symmetric Affine Camera,
IEICE(E90-D), No. 5, May 2007, pp. 851-858.
DOI Link
0705
BibRef
Earlier:
ECCV06(IV: 147-158).
Springer DOI
0608
BibRef
Ackermann, H.[Hanno],
Kanatani, K.[Kenichi],
Iterative Low Complexity Factorization for Projective Reconstruction,
RobVis08(153-164).
Springer DOI
0802
BibRef
Boutsidis, C.,
Gallopoulos, E.,
SVD based initialization:
A head start for nonnegative matrix factorization,
PR(41), No. 4, April 2008, pp. 1350-1362.
Elsevier DOI
0801
NMF, Sparse NMF, SVD, Nonnegative matrix factorization,
Singular value decomposition, Perron-Frobenius, Low rank,
Structured initialization, Sparse factorization
BibRef
Cichocki, A.[Andrzej],
Lee, H.Y.[Hyek-Young],
Kim, Y.D.[Yong-Deok],
Choi, S.J.[Seung-Jin],
Non-negative matrix factorization with alpha-divergence,
PRL(29), No. 9, 1 July 2008, pp. 1433-1440.
Elsevier DOI
0711
alpha-Divergence, Multiplicative updates,
Non-negative matrix factorization, Projected gradient
BibRef
Zhao, Q.,
Zhang, L.,
Cichocki, A.,
Bayesian CP Factorization of Incomplete Tensors with Automatic Rank
Determination,
PAMI(37), No. 9, September 2015, pp. 1751-1763.
IEEE DOI
1508
Approximation methods
BibRef
Lee, H.K.[Hye-Kyoung],
Yoo, J.H.[Ji-Ho],
Choi, S.J.[Seung-Jin],
Semi-Supervised Nonnegative Matrix Factorization,
SPLetters(17), No. 1, January 2010, pp. 4-7.
IEEE DOI
0911
BibRef
Khelifi, F.,
Jiang, J.,
Analysis of the Security of Perceptual Image Hashing Based on
Non-Negative Matrix Factorization,
SPLetters(17), No. 1, January 2010, pp. 43-46.
IEEE DOI
0911
BibRef
Khelifi, F.,
Jiang, J.,
Perceptual Image Hashing Based on Virtual Watermark Detection,
IP(19), No. 4, April 2010, pp. 981-994.
IEEE DOI
1003
BibRef
Ding, C.H.Q.[Chris H.Q.],
Li, T.[Tao],
Jordan, M.I.[Michael I.],
Convex and Semi-Nonnegative Matrix Factorizations,
PAMI(32), No. 1, January 2010, pp. 45-55.
IEEE DOI
0912
Explore the different solutions.
BibRef
Wahlberg, B.,
Stoica, P.,
New Square-Root Factorization of Inverse Toeplitz Matrices,
SPLetters(17), No. 2, February 2010, pp. 137-140.
IEEE DOI
0912
From the theory of rational orthonormal functions to derive
square-root factorizations of inverse of nXn positive definite Toeplitz matrix.
BibRef
Gillis, N.[Nicolas],
Glineur, F.[Francois],
Using underapproximations for sparse nonnegative matrix factorization,
PR(43), No. 4, April 2010, pp. 1676-1687.
Elsevier DOI
1002
Nonnegative matrix factorization, Underapproximation, Maximum edge
biclique problem, Sparsity, Image processing
BibRef
Gillis, N.,
Vavasis, S.A.,
Fast and Robust Recursive Algorithms for Separable Nonnegative Matrix
Factorization,
PAMI(36), No. 4, April 2014, pp. 698-714.
IEEE DOI
1404
Algorithm design and analysis
BibRef
Gillis, N.,
Successive Nonnegative Projection Algorithm for Robust Nonnegative
Blind Source Separation,
SIIMS(7), No. 2, 2014, pp. 1420-1450.
DOI Link
1407
BibRef
Li, Z.[Zhao],
Wu, X.D.[Xin-Dong],
Peng, H.[Hong],
Nonnegative Matrix Factorization on Orthogonal Subspace,
PRL(31), No. 9, 1 July 2010, pp. 905-911.
Elsevier DOI
1004
Nonnegative Matrix Factorization, Orthogonality, Clustering
BibRef
Zhao, K.[Keke],
Zhang, Z.Y.[Zhen-Yue],
Successively alternate least square for low-rank matrix factorization
with bounded missing data,
CVIU(114), No. 10, October 2010, pp. 1084-1096.
Elsevier DOI
1003
Matrix complement, Matrix factorization, Missing data, Low-rank
matrix, 3D reconstruction
BibRef
Zhang, Z.Y.[Zhen-Yue],
Zhao, K.[Keke],
Low-Rank Matrix Approximation with Manifold Regularization,
PAMI(35), No. 7, 2013, pp. 1717-1729.
IEEE DOI
1307
graph theory, matrix decomposition;
Symmetric matrices, manifold learning
BibRef
Yang, L.[Lei],
Hao, P.W.[Peng-Wei],
Wu, D.P.[Da-Peng],
Stabilization and optimization of PLUS factorization and its
application in image coding,
JVCIR(22), No. 1, January 2011, pp. 9-22.
Elsevier DOI
1101
PLUS factorization, Stable algorithm, Optimization, Transform coding;
Image compression, Integer reversible transform, Lapped Transform;
Discrete cosine transform, Lifting factorization
BibRef
Decherchi, S.[Sergio],
Gastaldo, P.[Paolo],
Zunino, R.[Rodolfo],
Efficient approximate Regularized Least Squares by Toeplitz matrix,
PRL(32), No. 3, 1 February 2011, pp. 468-475.
Elsevier DOI
1101
Regularized Least Squares, Toeplitz matrix, Levinson-Trench-Zohar
algorithm, Digital signal processor, Large-scale learning, Resources
limited device
BibRef
Sandler, R.[Roman],
Lindenbaum, M.[Michael],
Nonnegative Matrix Factorization with Earth Mover's Distance Metric for
Image Analysis,
PAMI(33), No. 8, August 2011, pp. 1590-1602.
IEEE DOI
1107
BibRef
Earlier:
Nonnegative Matrix Factorization with Earth Mover's Distance metric,
CVPR09(1873-1880).
IEEE DOI
0906
BibRef
Guan, N.Y.[Nai-Yang],
Tao, D.C.[Da-Cheng],
Luo, Z.G.[Zhi-Gang],
Yuan, B.[Bo],
Manifold Regularized Discriminative Nonnegative Matrix Factorization
With Fast Gradient Descent,
IP(20), No. 7, July 2011, pp. 2030-2048.
IEEE DOI
1107
BibRef
Ambai, M.[Mitsuru],
Utama, N.P.[Nugraha P.],
Yoshida, Y.[Yuichi],
Dimensionality Reduction for Histogram Features Based on Supervised
Non-negative Matrix Factorization,
IEICE(E94-D), No. 10, October 2011, pp. 1870-1879.
WWW Link.
1110
BibRef
Pan, J.Y.[Ji-Yuan],
Zhang, J.S.[Jiang-She],
Large margin based nonnegative matrix factorization and partial least
squares regression for face recognition,
PRL(32), No. 14, 15 October 2011, pp. 1822-1835.
Elsevier DOI
1110
Face recognition, Nonnegative matrix factorization, Out-of-sample;
Feature extraction, Large margin learning
BibRef
Yokoya, N.,
Yairi, T.,
Iwasaki, A.,
Coupled Nonnegative Matrix Factorization Unmixing for Hyperspectral and
Multispectral Data Fusion,
GeoRS(50), No. 2, February 2012, pp. 528-537.
IEEE DOI
1201
BibRef
Yokoya, N.,
Chanussot, J.,
Iwasaki, A.,
Nonlinear Unmixing of Hyperspectral Data Using Semi-Nonnegative
Matrix Factorization,
GeoRS(52), No. 2, February 2014, pp. 1430-1437.
IEEE DOI
1402
geophysical image processing
BibRef
Shang, F.H.[Fan-Hua],
Jiao, L.C.,
Wang, F.[Fei],
Graph dual regularization non-negative matrix factorization for
co-clustering,
PR(45), No. 6, June 2012, pp. 2237-2250.
Elsevier DOI
1202
Low-rank matrix factorization, Non-negative matrix factorization
(NMF), Graph Laplacian, Graph dual regularization, Co-clustering
BibRef
Zheng, W.S.[Wei-Shi],
Lai, J.[JianHuang],
Liao, S.C.[Sheng-Cai],
He, R.[Ran],
Extracting non-negative basis images using pixel dispersion penalty,
PR(45), No. 8, August 2012, pp. 2912-2926.
Elsevier DOI
1204
Non-negative matrix factorization (NMF), Non-negativity constraint;
Spatially localized basis images, Feature extraction, Face image
analysis
BibRef
Liu, H.F.[Hai-Feng],
Wu, Z.H.[Zhao-Hui],
Cai, D.[Deng],
Huang, T.S.[Thomas S.],
Constrained Nonnegative Matrix Factorization for Image Representation,
PAMI(34), No. 7, July 2012, pp. 1299-1311.
IEEE DOI
1205
Nonnegative matrix factorization, semi-supervised learning, dimension
reduction, clustering.
BibRef
Liu, H.F.[Hai-Feng],
Yang, G.,
Wu, Z.H.[Zhao-Hui],
Cai, D.[Deng],
Constrained Concept Factorization for Image Representation,
Cyber(44), No. 7, July 2014, pp. 1214-1224.
IEEE DOI
1407
Algorithm design and analysis
BibRef
Kumar, B.G.V.[B.G. Vijay],
Kotsia, I.[Irene],
Patras, I.[Ioannis],
Max-margin Non-negative Matrix Factorization,
IVC(30), No. 4-5, May 2012, pp. 279-291.
Elsevier DOI
1206
Non-negative Matrix Factorization, Supervised feature extraction;
Semi-NMF, Max-margin classifier
BibRef
Gong, P.[Pinghua],
Zhang, C.S.[Chang-Shui],
Efficient Nonnegative Matrix Factorization via projected Newton method,
PR(45), No. 9, September 2012, pp. 3557-3565.
Elsevier DOI
1206
Nonnegative Matrix Factorization, Projected Newton method, Quadratic
convergence rate, Nonnegative least squares, Low rank
BibRef
Esser, E.,
Moller, M.,
Osher, S.,
Sapiro, G.,
Xin, J.,
A Convex Model for Nonnegative Matrix Factorization and Dimensionality
Reduction on Physical Space,
IP(21), No. 7, July 2012, pp. 3239-3252.
IEEE DOI
1206
BibRef
Shi, M.[Min],
Yi, Q.M.[Qing-Ming],
Lv, J.[Jun],
Symmetric Nonnegative Matrix Factorization With Beta-Divergences,
SPLetters(19), No. 8, August 2012, pp. 539-542.
IEEE DOI
1208
BibRef
Liu, Y.Y.[Yuan-Yuan],
Jiao, L.C.,
Shang, F.H.[Fan-Hua],
An efficient matrix factorization based low-rank representation for
subspace clustering,
PR(46), No. 1, January 2013, pp. 284-292.
Elsevier DOI
1209
Nuclear norm minimization (NNM), Low rank representation, Alternating
direction method (ADM), Matrix tri-factorization, Positive semidefinite
(PSD)
BibRef
Liu, Y.Y.[Yuan-Yuan],
Jiao, L.C.,
Shang, F.H.[Fan-Hua],
A fast tri-factorization method for low-rank matrix recovery and
completion,
PR(46), No. 1, January 2013, pp. 163-173.
Elsevier DOI
1209
Rank minimization, Nuclear norm minimization, Matrix completion;
Low-rank and sparse decomposition, Low rank representation
BibRef
Liu, Y.G.[Yi-Guang],
Liu, B.B.[Bing-Bing],
Pu, Y.F.[Yi-Fei],
Chen, X.H.[Xiao-Hui],
Cheng, H.[Hong],
Low-rank matrix decomposition in L1-norm by dynamic systems,
IVC(30), No. 11, November 2012, pp. 915-921.
Elsevier DOI
1211
Low-rank matrix approximation, Dynamic system, L_1 norm, Computational
efficiency
BibRef
Liu, Y.G.[Yi-Guang],
Cao, L.P.[Li-Ping],
Liu, C.L.[Chun-Ling],
Pu, Y.F.[Yi-Fei],
Cheng, H.[Hong],
Recovering shape and motion by a dynamic system for low-rank matrix
approximation in L_1 norm,
VC(29), No. 5, May 2013, pp. 421-431.
WWW Link.
1305
BibRef
Essid, S.,
Fevotte, C.,
Smooth Nonnegative Matrix Factorization for Unsupervised Audiovisual
Document Structuring,
MultMed(15), No. 2, 2013, pp. 415-425.
IEEE DOI
1302
BibRef
Tan, V.Y.F.,
Fevotte, C.,
Automatic Relevance Determination in Nonnegative Matrix Factorization
with the beta-Divergence,
PAMI(35), No. 7, 2013, pp. 1592-1605.
IEEE DOI
1307
matrix decomposition, latent dimensionality;
maximum a posteriori estimation;
nonnegative matrix factorization
BibRef
Wang, S.,
Quasi-Block-Cholesky Factorization With Dynamic Matrix Compression for
Fast Integral-Equation Simulations of Large-Scale Human Body Models,
PIEEE(100), No. 2, February 2013, pp. 389-400.
IEEE DOI
1302
BibRef
Kim, Y.D.[Yong-Deok],
Choi, S.J.[Seung-Jin],
Variational Bayesian View of Weighted Trace Norm Regularization for
Matrix Factorization,
SPLetters(20), No. 3, March 2013, pp. 261-264.
IEEE DOI
1303
BibRef
Kim, J.H.[Jae-Hean],
Koo, B.K.[Bon-Ki],
Factorization of canonic homographies for camera calibration and scene
modeling,
FCV13(5-10).
IEEE DOI
1304
BibRef
Wang, J.J.Y.[Jim Jing-Yan],
Bensmail, H.[Halima],
Gao, X.[Xin],
Multiple graph regularized nonnegative matrix factorization,
PR(46), No. 10, October 2013, pp. 2840-2847.
Elsevier DOI
1306
Data representation, Nonnegative matrix factorization, Graph
Laplacian, Ensemble manifold regularization
BibRef
Wang, J.Y.[Jing-Yan],
Almasri, I.[Islam],
Gao, X.[Xin],
Adaptive graph regularized Nonnegative Matrix Factorization via feature
selection,
ICPR12(963-966).
WWW Link.
1302
BibRef
Li, Z.C.[Ze-Chao],
Liu, J.[Jing],
Lu, H.Q.[Han-Qing],
Structure preserving non-negative matrix factorization for
dimensionality reduction,
CVIU(117), No. 9, 2013, pp. 1175-1189.
Elsevier DOI
1307
Dimensionality reduction
BibRef
Wang, L.[Lu],
Albera, L.,
Kachenoura, A.,
Shu, H.Z.[Hua-Zhong],
Senhadji, L.,
Nonnegative Joint Diagonalization by Congruence Based on LU Matrix
Factorization,
SPLetters(20), No. 8, 2013, pp. 807-810.
IEEE DOI
1307
NMR spectroscopy
BibRef
Li, J.[Jun],
Tao, D.C.[Da-Cheng],
A Bayesian Hierarchical Factorization Model for Vector Fields,
IP(22), No. 11, 2013, pp. 4510-4521.
IEEE DOI
1310
Bayes methods
BibRef
Wu, S.Y.[Shu-Yi],
Zhang, X.[Xiang],
Guan, N.Y.[Nai-Yang],
Tao, D.C.[Da-Cheng],
Huang, X.H.[Xu-Hui],
Luo, Z.G.[Zhi-Gang],
Non-negative Low-Rank and Group-Sparse Matrix Factorization,
MMMod15(II: 536-547).
Springer DOI
1501
BibRef
Xu, Y.,
Yin, W.,
A Block Coordinate Descent Method for Regularized Multiconvex
Optimization with Applications to Nonnegative Tensor Factorization
and Completion,
SIIMS(6), No. 3, 2013, pp. 1758-1789.
DOI Link
1310
BibRef
Hu, L.[Lirui],
Dai, L.[Liang],
Wu, J.G.[Jian-Guo],
Convergent Projective Non-negative Matrix Factorization with
Kullback-Leibler Divergence,
PRL(36), No. 1, 2014, pp. 15-21.
Elsevier DOI
1312
Projective Non-negative Matrix Factorization
BibRef
Hu, L.[Lirui],
Wu, N.[Ning],
Li, X.[Xiao],
Feature Nonlinear Transformation Non-Negative Matrix Factorization
with Kullback-Leibler Divergence,
PR(132), 2022, pp. 108906.
Elsevier DOI
2209
Non-negative matrix factorization, Nonlinear transformation,
Feature extraction, Object recognition, Clustering, Kullback-Leibler divergence
BibRef
Ye, J.[Jun],
Jin, Z.[Zhong],
Non-negative matrix factorisation based on fuzzy K nearest neighbour
graph and its applications,
IET-CV(7), No. 5, October 2013, pp. 346-353.
DOI Link
1402
face recognition
BibRef
Zou, W.B.[Wen-Bin],
Bai, C.[Cong],
Kpalma, K.,
Ronsin, J.,
Online Glocal Transfer for Automatic Figure-Ground Segmentation,
IP(23), No. 5, May 2014, pp. 2109-2121.
IEEE DOI
1405
Markov processes
BibRef
Zou, W.B.[Wen-Bin],
Kpalma, K.[Kidiyo],
Liu, Z.[Zhi],
Ronsin, J.[Joseph],
Segmentation Driven Low-rank Matrix Recovery for Saliency Detection,
BMVC13(xx-yy).
DOI Link
1402
BibRef
Zhou, G.X.[Guo-Xu],
Cichocki, A.,
Zhao, Q.B.[Qi-Bin],
Xie, S.L.[Sheng-Li],
Nonnegative Matrix and Tensor Factorizations:
An algorithmic perspective,
SPMag(31), No. 3, May 2014, pp. 54-65.
IEEE DOI
1405
Approximation methods
BibRef
Zhou, G.X.[Guo-Xu],
Cichocki, A.,
Zhao, Q.B.[Qi-Bin],
Xie, S.L.[Sheng-Li],
Efficient Nonnegative Tucker Decompositions:
Algorithms and Uniqueness,
IP(24), No. 12, December 2015, pp. 4990-5003.
IEEE DOI
1512
approximation theory
BibRef
Huang, K.,
Sidiropoulos, N.,
Putting Nonnegative Matrix Factorization to the Test: A tutorial
derivation of pertinent Cramer-Rao bounds and performance
benchmarking,
SPMag(31), No. 3, May 2014, pp. 76-86.
IEEE DOI
1405
Cramer-Rao bounds
BibRef
Feng, J.Z.[Jian-Zhou],
Huo, X.M.[Xiao-Ming],
Song, L.[Li],
Yang, X.K.[Xiao-Kang],
Zhang, W.J.[Wen-Jun],
Evaluation of Different Algorithms of Nonnegative Matrix
Factorization in Temporal Psychovisual Modulation,
CirSysVideo(24), No. 4, April 2014, pp. 553-565.
IEEE DOI
1405
least squares approximations
BibRef
Li, Z.C.[Ze-Chao],
Liu, J.[Jing],
Tang, J.H.[Jin-Hui],
Lu, H.Q.[Han-Qing],
Projective Matrix Factorization with unified embedding for social
image tagging,
CVIU(124), No. 1, 2014, pp. 71-78.
Elsevier DOI
1406
Projective Matrix Factorization
BibRef
Li, Z.C.[Ze-Chao],
Tang, J.H.[Jin-Hui],
Weakly Supervised Deep Matrix Factorization for Social Image
Understanding,
IP(26), No. 1, January 2017, pp. 276-288.
IEEE DOI
1612
gradient methods
BibRef
Gonen, M.,
Kaski, S.,
Kernelized Bayesian Matrix Factorization,
PAMI(36), No. 10, October 2014, pp. 2047-2060.
IEEE DOI
1410
approximation theory
BibRef
Yang, Z.R.[Zhi-Rong],
Oja, E.[Erkki],
Quadratic nonnegative matrix factorization,
PR(45), No. 4, 2012, pp. 1500-1510.
Elsevier DOI
1410
Nonnegative matrix factorization
BibRef
Szabó, Z.[Zoltán],
Póczos, B.[Barnabás],
Lorincz, A.[András],
Separation theorem for independent subspace analysis and its
consequences,
PR(45), No. 4, 2012, pp. 1782-1791.
Elsevier DOI
1410
BibRef
And:
Online group-structured dictionary learning,
CVPR11(2865-2872).
IEEE DOI
1106
Separation principles.
Implement for
the online, structured, sparse non-negative matrix factorization.
BibRef
Liu, X.B.[Xiao-Bai],
Xu, Q.[Qian],
Yan, S.C.[Shui-Cheng],
Wang, G.[Gang],
Jin, H.[Hai],
Lee, S.W.[Seong-Whan],
Nonnegative Tensor Cofactorization and Its Unified Solution,
IP(23), No. 9, September 2014, pp. 3950-3961.
IEEE DOI
1410
convergence
BibRef
Chen, Q.A.[Qi-Ang],
Yan, S.C.[Shui-Cheng],
Ng, T.T.[Tian-Tsong],
Factorization towards a classifier,
CVPR10(3562-3569).
IEEE DOI
1006
BibRef
Liao, S.C.[Sheng-Cai],
Lei, Z.[Zhen],
Li, S.Z.[Stan Z.],
Nonnegative Matrix Factorization with Gibbs Random Field modeling,
Subspace09(79-86).
IEEE DOI
0910
BibRef
Li, B.[Bo],
Zhou, G.X.[Guo-Xu],
Cichocki, A.,
Two Efficient Algorithms for Approximately Orthogonal Nonnegative
Matrix Factorization,
SPLetters(22), No. 7, July 2015, pp. 843-846.
IEEE DOI
1412
gradient methods
BibRef
Jin, T.S.[Tai-Song],
Yu, J.[Jun],
You, J.[Jane],
Zeng, K.[Kun],
Li, C.H.[Cui-Hua],
Yu, Z.T.[Zheng-Tao],
Low-rank matrix factorization with multiple Hypergraph regularizer,
PR(48), No. 3, 2015, pp. 1011-1022.
Elsevier DOI
1412
Hypergraph
BibRef
Rapin, J.[Jérémy],
Bobin, J.[Jérôme],
Larue, A.[Anthony],
Starck, J.L.[Jean-Luc],
NMF with Sparse Regularizations in Transformed Domains,
SIIMS(7), No. 4, 2014, pp. 2020-2047.
DOI Link
1412
BibRef
And: A2, A4, A1, A3:
Sparse blind source separation for partially correlated sources,
ICIP14(6021-6025)
IEEE DOI
1502
Nonnegative matrix factorization.
Algorithm design and analysis
BibRef
Sun, M.[Meng],
Zhang, X.W.[Xiong-Wei],
van Hamme, H.[Hugo],
A stable approach for model order selection in nonnegative matrix
factorization,
PRL(54), No. 1, 2015, pp. 97-102.
Elsevier DOI
1502
Model order selection
BibRef
Mirzaei, S.[Sayeh],
van Hamme, H.[Hugo],
Khosravani, S.[Shima],
Hyperspectral image classification using Non-negative Tensor
Factorization and 3D Convolutional Neural Networks,
SP:IC(76), 2019, pp. 178-185.
Elsevier DOI
1906
Hyperspectral image classification,
Non-negative Tensor Factorization (NTF), Convolutional Neural Network (CNN)
BibRef
Han, H.[Hong],
Liu, S.J.[San-Jun],
Gan, L.[Lu],
Non-negativity and dependence constrained sparse coding for image
classification,
JVCIR(26), No. 1, 2015, pp. 247-254.
Elsevier DOI
1502
Non-negative Matrix Factorization
BibRef
Ye, M.C.[Min-Chao],
Qian, Y.T.[Yun-Tao],
Zhou, J.[Jun],
Multitask Sparse Nonnegative Matrix Factorization for Joint
Spectral-Spatial Hyperspectral Imagery Denoising,
GeoRS(53), No. 5, May 2015, pp. 2621-2639.
IEEE DOI
1502
geophysical image processing
BibRef
Xiong, F.C.[Feng-Chao],
Qian, Y.T.[Yun-Tao],
Zhou, J.[Jun],
Tang, Y.Y.[Yuan Yan],
Hyperspectral Unmixing via Total Variation Regularized Nonnegative
Tensor Factorization,
GeoRS(57), No. 4, April 2019, pp. 2341-2357.
IEEE DOI
1904
BibRef
Earlier: A1, A3, A2, Only:
Hyperspectral Imagery Denoising via Reweighed Sparse Low-Rank
Nonnegative Tensor Factorization,
ICIP18(3219-3223)
IEEE DOI
1809
hyperspectral imaging, matrix decomposition, tensors,
hyperspectral unmixing, local spatial information,
total variation (TV).
Noise reduction, Tensile stress, Sparse matrices,
Image restoration, Hyperspectral imaging, Image coding,
low-rank representation
BibRef
Xiong, F.C.[Feng-Chao],
Zhou, J.[Jun],
Qian, Y.T.[Yun-Tao],
Hyperspectral Restoration via L_0 Gradient Regularized Low-Rank
Tensor Factorization,
GeoRS(57), No. 12, December 2019, pp. 10410-10425.
IEEE DOI
1912
Noise reduction, Image restoration, Hyperspectral imaging,
Matrix decomposition, Correlation, Sparse matrices,
spectral-spatial information
BibRef
Xu, F.[Fan],
Bai, X.[Xiao],
Zhou, J.[Jun],
Non-local similarity based tensor decomposition for hyperspectral
image denoising,
ICIP17(1890-1894)
IEEE DOI
1803
Hyperspectral imaging, Image denoising, Noise reduction,
Tensile stress,
Tensor Decomposition
BibRef
Ma, Z.,
Teschendorff, A.E.,
Leijon, A.,
Qiao, Y.,
Zhang, H.,
Guo, J.,
Variational Bayesian Matrix Factorization for Bounded Support Data,
PAMI(37), No. 4, April 2015, pp. 876-889.
IEEE DOI
1503
Approximation methods
BibRef
Jiang, F.Y.[Fang-Yuan],
Enqvist, O.[Olof],
Kahl, F.[Fredrik],
A Combinatorial Approach to L1 -Matrix Factorization,
JMIV(51), No. 3, March 2015, pp. 430-441.
WWW Link.
1504
BibRef
Qiao, H.L.[Han-Li],
New SVD based initialization strategy for non-negative matrix
factorization,
PRL(63), No. 1, 2015, pp. 71-77.
Elsevier DOI
1508
NMF
BibRef
Liu, Y.,
Lei, Y.,
Li, C.,
Xu, W.,
Pu, Y.,
A Random Algorithm for Low-Rank Decomposition of Large-Scale Matrices
With Missing Entries,
IP(24), No. 11, November 2015, pp. 4502-4511.
IEEE DOI
1509
Approximation algorithms
BibRef
Wu, Y.W.[Yu-Wei],
Jia, Y.D.[Yun-De],
Li, P.H.[Pei-Hua],
Zhang, J.[Jian],
Yuan, J.S.[Jun-Song],
Manifold Kernel Sparse Representation of Symmetric Positive-Definite
Matrices and Its Applications,
IP(24), No. 11, November 2015, pp. 3729-3741.
IEEE DOI
1509
graph theory
BibRef
El Aziz, M.A.[Mohamed Abd],
Khidr, W.[Wael],
Nonnegative matrix factorization based on projected hybrid conjugate
gradient algorithm,
SIViP(9), No. 8, November 2015, pp. 1825-1831.
WWW Link.
1511
BibRef
Rad, R.[Roya],
Jamzad, M.[Mansour],
Automatic image annotation by a loosely joint non-negative matrix
factorisation,
IET-CV(9), No. 6, 2015, pp. 806-813.
DOI Link
1512
image classification
BibRef
Rad, R.[Roya],
Jamzad, M.[Mansour],
Image annotation using multi-view non-negative matrix factorization
with different number of basis vectors,
JVCIR(46), No. 1, 2017, pp. 1-12.
Elsevier DOI
1706
Automatic, image, annotation
BibRef
Simsekli, U.,
Liutkus, A.,
Cemgil, A.T.,
Alpha-Stable Matrix Factorization,
SPLetters(22), No. 12, December 2015, pp. 2289-2293.
IEEE DOI
1512
Markov processes
BibRef
Yang, L.[Liu],
Jing, L.P.[Li-Ping],
Ng, M.K.,
Robust and Non-Negative Collective Matrix Factorization for
Text-to-Image Transfer Learning,
IP(24), No. 12, December 2015, pp. 4701-4714.
IEEE DOI
1512
convergence of numerical methods
BibRef
Wang, D.,
Gao, X.,
Wang, X.,
Semi-Supervised Nonnegative Matrix Factorization via Constraint
Propagation,
Cyber(46), No. 1, January 2016, pp. 233-244.
IEEE DOI
1601
Approximation methods
BibRef
Fu, X.[Xiao],
Ma, W.K.[Wing-Kin],
Robustness Analysis of Structured Matrix Factorization via
Self-Dictionary Mixed-Norm Optimization,
SPLetters(23), No. 1, January 2016, pp. 60-64.
IEEE DOI
1601
matrix decomposition
BibRef
Mao, J.Y.[Jia-Yun],
Zhang, Z.Y.[Zhen-Yue],
A local convex method for rank-sparsity factorization,
PRL(71), No. 1, 2016, pp. 31-37.
Elsevier DOI
1602
Low-rank matrices
BibRef
Li, X.[Xue],
Shen, B.[Bin],
Liu, B.D.[Bao-Di],
Zhang, Y.J.[Yu-Jin],
A Locality Sensitive Low-Rank Model for Image Tag Completion,
MultMed(18), No. 3, March 2016, pp. 474-483.
IEEE DOI
1603
BibRef
Earlier: A1, A4, A2, A3:
Image tag completion by low-rank factorization with dual
reconstruction structure preserved,
ICIP14(3062-3066)
IEEE DOI
1502
Computational modeling.
Encoding
BibRef
Li, X.[Xue],
Shen, B.[Bin],
Liu, B.D.[Bao-Di],
Zhang, Y.J.[Yu-Jin],
Ranking-Preserving Low-Rank Factorization for Image Annotation With
Missing Labels,
MultMed(20), No. 5, May 2018, pp. 1169-1178.
IEEE DOI
1805
Correlation, Matrix decomposition, Predictive models,
Sparse matrices, Training, Visualization,
tag ranking
BibRef
Shen, B.[Bin],
Liu, B.D.[Bao-Di],
Wang, Q.F.[Qi-Fan],
Ji, R.R.[Rong-Rong],
Robust nonnegative matrix factorization via L1 norm regularization by
multiplicative updating rules,
ICIP14(5282-5286)
IEEE DOI
1502
Additive noise
BibRef
Lu, G.F.,
Wang, Y.,
Zou, J.,
Low-Rank Matrix Factorization With Adaptive Graph Regularizer,
IP(25), No. 5, May 2016, pp. 2196-2205.
IEEE DOI
1604
data structures
BibRef
Arjona Ramírez, M.,
Non-Negative Temporal Decomposition Regularization With an Augmented
Lagrangian,
SPLetters(23), No. 5, May 2016, pp. 663-667.
IEEE DOI
1604
Cost function
BibRef
Zhu, F.,
Honeine, P.,
Biobjective Nonnegative Matrix Factorization:
Linear Versus Kernel-Based Models,
GeoRS(54), No. 7, July 2016, pp. 4012-4022.
IEEE DOI
1606
Biological system modeling
BibRef
Tang, J.,
Wang, K.,
Shao, L.,
Supervised Matrix Factorization Hashing for Cross-Modal Retrieval,
IP(25), No. 7, July 2016, pp. 3157-3166.
IEEE DOI
1606
computational complexity
BibRef
Zhu, M.,
Miao, H.,
Tang, J.,
Multi-Kernel Supervised Hashing with Graph Regularization for
Cross-Modal Retrieval,
ICPR18(2717-2722)
IEEE DOI
1812
Kernel, Semantics, Optimization, Linear programming, Correlation,
Signal processing
BibRef
Shokrollahi, M.[Mehrnaz],
Krishnan, S.[Sridhar],
Non-stationary signal feature characterization using adaptive
dictionaries and non-negative matrix factorization,
SIViP(10), No. 6, June 2016, pp. 1025-1032.
WWW Link.
1608
BibRef
Babaee, M.[Mohammadreza],
Wolf, T.[Thomas],
Rigoll, G.[Gerhard],
Toward semantic attributes in dictionary learning and non-negative
matrix factorization,
PRL(80), No. 1, 2016, pp. 172-178.
Elsevier DOI
1609
BibRef
And:
Relative attribute guided dictionary learning,
ICIP16(704-708)
IEEE DOI
1610
Clustering algorithms
Dictionary
BibRef
Babaee, M.[Mohammadreza],
Bahmanyar, R.[Reza],
Rigoll, G.[Gerhard],
Datcu, M.[Mihai],
Farness preserving Non-negative matrix factorization,
ICIP14(3023-3027)
IEEE DOI
1502
Accuracy
BibRef
Cao, X.,
Zhao, Q.,
Meng, D.,
Chen, Y.,
Xu, Z.,
Robust Low-Rank Matrix Factorization Under General Mixture Noise
Distributions,
IP(25), No. 10, October 2016, pp. 4677-4690.
IEEE DOI
1610
Gaussian distribution
BibRef
Cao, X.,
Chen, Y.,
Zhao, Q.,
Meng, D.,
Wang, Y.,
Wang, D.,
Xu, Z.,
Low-Rank Matrix Factorization under General Mixture Noise
Distributions,
ICCV15(1493-1501)
IEEE DOI
1602
Adaptation models
BibRef
Ding, G.G.[Gui-Guang],
Guo, Y.C.[Yu-Chen],
Zhou, J.[Jile],
Gao, Y.,
Large-Scale Cross-Modality Search via Collective Matrix Factorization
Hashing,
IP(25), No. 11, November 2016, pp. 5427-5440.
IEEE DOI
1610
BibRef
Earlier: A1, A2, A3, Only:
Collective Matrix Factorization Hashing for Multimodal Data,
CVPR14(2083-2090)
IEEE DOI
1409
Algorithm design and analysis
BibRef
Zhang, G.,
Gong, X.,
Nonnegative Matrix Cofactorization for Weakly Supervised Image
Parsing,
SPLetters(23), No. 11, November 2016, pp. 1682-1686.
IEEE DOI
1609
image segmentation
BibRef
Trigeorgis, G.[George],
Bousmalis, K.[Konstantinos],
Zafeiriou, S.P.[Stefanos P.],
Schuller, B.W.[Björn W.],
A Deep Matrix Factorization Method for Learning Attribute
Representations,
PAMI(39), No. 3, March 2017, pp. 417-429.
IEEE DOI
1702
Algorithm design and analysis
See also Deep Canonical Time Warping.
BibRef
Kumar, V.[Vikas],
Pujari, A.K.[Arun K.],
Sahu, S.K.[Sandeep Kumar],
Kagita, V.R.[Venkateswara Rao],
Padmanabhan, V.[Vineet],
Proximal maximum margin matrix factorization for collaborative
filtering,
PRL(86), No. 1, 2017, pp. 62-67.
Elsevier DOI
1702
Collaborative filtering
BibRef
Karoui, M.S.,
Deville, Y.,
Benhalouche, F.Z.,
Boukerch, I.,
Hypersharpening by Joint-Criterion Nonnegative Matrix Factorization,
GeoRS(55), No. 3, March 2017, pp. 1660-1670.
IEEE DOI
1703
Algorithm design and analysis
BibRef
Hou, J.,
Chau, L.P.,
Magnenat-Thalmann, N.,
He, Y.,
Sparse Low-Rank Matrix Approximation for Data Compression,
CirSysVideo(27), No. 5, May 2017, pp. 1043-1054.
IEEE DOI
1705
Approximation error, Coherence, Data compression,
Matrix decomposition, Sparse matrices, Transforms,
Data compression, low-rank matrix, optimization,
orthogonal transform, sparsity
BibRef
Debals, O.,
van Barel, M.,
de Lathauwer, L.,
Nonnegative Matrix Factorization Using Nonnegative Polynomial
Approximations,
SPLetters(24), No. 7, July 2017, pp. 948-952.
IEEE DOI
1706
Approximation algorithms, Convergence, Optimization,
Signal processing algorithms, Standards, TV,
Nonnegative matrix factorization (NMF),
nonnegative polynomials, polynomial, approximation
BibRef
Ma, X.K.[Xiao-Ke],
Sun, P.G.[Peng-Gang],
Qin, G.M.[Gui-Min],
Nonnegative matrix factorization algorithms for link prediction in
temporal networks using graph communicability,
PR(71), No. 1, 2017, pp. 361-374.
Elsevier DOI
1707
Dynamic, networks
BibRef
Lu, Y.,
Yuan, C.,
Lai, Z.,
Li, X.,
Wong, W.K.,
Zhang, D.,
Nuclear Norm-Based 2DLPP for Image Classification,
MultMed(19), No. 11, November 2017, pp. 2391-2403.
IEEE DOI
1710
Two-dimensional locality preserving projections.
Face recognition, Feature extraction, Image reconstruction,
Manifolds, Principal component analysis, Robustness,
BibRef
Lu, Y.[Yuwu],
Lai, Z.H.[Zhi-Hui],
Li, X.L.[Xue-Long],
Zhang, D.[David],
Wong, W.K.[Wai Keung],
Yuan, C.[Chun],
Learning Parts-Based and Global Representation for Image
Classification,
CirSysVideo(28), No. 12, December 2018, pp. 3345-3360.
IEEE DOI
1812
Robustness, Sparse matrices, Matrix decomposition,
Image classification, Manifolds, Euclidean distance, Geometry,
image classification
BibRef
Yuan, Y.,
Li, X.L.,
Pang, Y.,
Lu, X.,
Tao, D.,
Binary Sparse Nonnegative Matrix Factorization,
CirSysVideo(19), No. 5, May 2009, pp. 772-777.
IEEE DOI
0906
BibRef
Lu, Y.W.[Yu-Wu],
Yuan, C.[Chun],
Zhu, W.W.[Wen-Wu],
Li, X.L.[Xue-Long],
Structurally Incoherent Low-Rank Nonnegative Matrix Factorization for
Image Classification,
IP(27), No. 11, November 2018, pp. 5248-5260.
IEEE DOI
1809
image classification, learning (artificial intelligence),
matrix decomposition, visual databases, image classification,
BibRef
Lu, Y.,
Yuan, C.,
Li, X.,
Lai, Z.,
Zhang, D.,
Shen, L.,
Structurally Incoherent Low-Rank 2DLPP for Image Classification,
CirSysVideo(29), No. 6, June 2019, pp. 1701-1714.
IEEE DOI
1906
Feature extraction, Image classification, Robustness, Kernel,
structurally incoherent
BibRef
Lu, Y.,
Lai, Z.,
Xu, Y.,
Li, X.,
Zhang, D.,
Yuan, C.,
Nonnegative Discriminant Matrix Factorization,
CirSysVideo(27), No. 7, July 2017, pp. 1392-1405.
IEEE DOI
1707
Convergence, Euclidean distance, Image classification,
Image reconstruction, Linear programming, Matrix decomposition,
Principal component analysis, Discriminative ability,
face recognition, maximum margin criterion (MMC), nonnegative,
matrix, factorization, (NMF)
BibRef
Zhu, X.X.[Xiang-Xiang],
Zhang, Z.S.[Zhuo-Sheng],
Improved self-paced learning framework for nonnegative matrix
factorization,
PRL(97), No. 1, 2017, pp. 1-7.
Elsevier DOI
1709
Nonnegative matrix factorization
BibRef
Leng, C.C.[Cheng-Cai],
Cai, G.R.[Guo-Rong],
Yu, D.D.[Dong-Dong],
Wang, Z.Y.[Zong-Yue],
Adaptive total-variation for non-negative matrix factorization on
manifold,
PRL(98), No. 1, 2017, pp. 68-74.
Elsevier DOI
1710
Adaptive total variation
BibRef
Lin, Z.C.[Zhou-Chen],
Xu, C.[Chen],
Zha, H.B.[Hong-Bin],
Robust Matrix Factorization by Majorization Minimization,
PAMI(40), No. 1, January 2018, pp. 208-220.
IEEE DOI
1712
Algorithm design and analysis, Convergence,
Linear programming, Minimization, Robustness, Scalability,
majorization minimization
BibRef
Duong, V.H.[Viet-Hang],
Bui, M.Q.[Manh-Quan],
Ding, J.J.[Jian-Jiun],
Lee, Y.S.[Yuan-Shan],
Pham, B.T.[Bach-Tung],
Bao, P.T.[Pham The],
Wang, J.C.[Jia-Ching],
A New Approach of Matrix Factorization on Complex Domain for Data
Representation,
IEICE(E100-D), No. 12, December 2017, pp. 3059-3063.
WWW Link.
1712
BibRef
Chepuri, S.P.,
Factor Analysis From Quadratic Sampling,
SPLetters(25), No. 1, January 2018, pp. 65-69.
IEEE DOI
1801
covariance matrices, iterative methods, matrix decomposition,
signal sampling, statistical analysis,
stochastic gradient descent
BibRef
Fu, X.,
Huang, K.,
Sidiropoulos, N.D.,
On Identifiability of Nonnegative Matrix Factorization,
SPLetters(25), No. 3, March 2018, pp. 328-332.
IEEE DOI
1802
Data models, Hyperspectral sensors, Indexes, Matrix decomposition,
Science - general, Sensors, US Government, Convex analysis,
sufficiently scattered
BibRef
Chen, J.Z.[Jia-Zhong],
Chen, J.[Jie],
Ling, H.[Hefei],
Cao, H.[Hua],
Sun, W.P.[Wei-Ping],
Fan, Y.B.[Ye-Bin],
Wu, W.M.[Wei-Min],
Salient object detection via spectral graph weighted low rank matrix
recovery,
JVCIR(50), 2018, pp. 270-279.
Elsevier DOI
1802
Saliency detection, Spectral graph, Low rank matrix recovery,
Sparse decomposition, Feature matrix
BibRef
Huang, S.[Sheng],
Wang, H.X.[Hong-Xing],
Ge, Y.X.[Yong-Xin],
Huangfu, L.[Luwen],
Zhang, X.H.[Xiao-Hong],
Yang, D.[Dan],
Improved hypergraph regularized Nonnegative Matrix Factorization with
sparse representation,
PRL(102), 2018, pp. 8-14.
Elsevier DOI
1802
Nonnegative Matrix Factorization, Image representation,
Hypergraph learning, Image clustering,
Sparse representation
BibRef
Zhu, W.J.[Wen-Jie],
Yan, Y.H.[Yun-Hui],
Label and orthogonality regularized non-negative matrix factorization
for image classification,
SP:IC(62), 2018, pp. 139-148.
Elsevier DOI
1802
Non-negative matrix factorization (NMF), Orthogonal property,
Label consistence, Image classification
BibRef
Zhu, W.J.[Wen-Jie],
Yan, Y.H.[Yun-Hui],
Non-negative matrix factorization via discriminative label embedding
for pattern classification,
JVCIR(55), 2018, pp. 477-488.
Elsevier DOI
1809
Non-negative matrix factorization (NMF),
Discriminative label embedding, Orthogonality constraint.
BibRef
Tan, Q.[Qi],
Yang, P.[Pei],
He, J.R.[Jing-Rui],
Feature co-shrinking for co-clustering,
PR(77), 2018, pp. 12-19.
Elsevier DOI
1802
Co-clustering, Non-negative matrix tri-factorization,
Co-sparsity, Co-feature-selection
BibRef
Erichson, N.B.[N. Benjamin],
Mendible, A.[Ariana],
Wihlborn, S.[Sophie],
Kutz, J.N.[J. Nathan],
Randomized nonnegative matrix factorization,
PRL(104), 2018, pp. 1-7.
Elsevier DOI
1804
NMF, Randomized algorithm, Dimension reduction
BibRef
Markopoulos, P.P.,
Chachlakis, D.G.,
Papalexakis, E.E.,
The Exact Solution to Rank-1 L1-Norm TUCKER2 Decomposition,
SPLetters(25), No. 4, April 2018, pp. 511-515.
IEEE DOI
1804
computational complexity, matrix decomposition, tensors,
3-way tensors, L1-norm TUCKER2 decomposition, NP-hard problem,
tensors
BibRef
Fang, Y.X.[Yi-Xian],
Zhang, H.X.[Hua-Xiang],
Ren, Y.W.[Yu-Wei],
Graph regularised sparse NMF factorisation for imagery de-noising,
IET-CV(12), No. 4, June 2018, pp. 466-475.
DOI Link
1805
BibRef
Fang, Y.X.[Yi-Xian],
Ren, Y.W.[Yu-Wei],
Zhang, H.X.[Hua-Xiang],
Semantic convex matrix factorisation for cross-media retrieval,
IET-IPR(13), No. 1, January 2019, pp. 196-205.
DOI Link
1812
BibRef
Wen, J.[Jie],
Zhang, B.[Bob],
Xu, Y.[Yong],
Yang, J.[Jian],
Han, N.[Na],
Adaptive weighted nonnegative low-rank representation,
PR(81), 2018, pp. 326-340.
Elsevier DOI
1806
Low-rank representation, Adaptive weighted matrix,
Data clustering, Locality constraint
BibRef
Song, M.H.[Ming-Hui],
Peng, Y.X.[Yuan-Xi],
Jiang, T.[Tian],
Li, J.[Jun],
Zhang, S.S.[Song-Song],
Accelerated image factorization based on improved NMF algorithm,
RealTimeIP(15), No. 1, June 2018, pp. 93-105.
Springer DOI
1806
BibRef
Chen, Y.,
Zhang, H.,
Zhang, X.,
Liu, R.,
Regularized Semi-non-negative Matrix Factorization for Hashing,
MultMed(20), No. 7, July 2018, pp. 1823-1836.
IEEE DOI
1806
Algorithm design and analysis, Binary codes,
Computational modeling, Encoding, Measurement, Optimization,
stochastic learning
BibRef
He, Z.,
Yuan, X.,
Block Iteratively Reweighted Algorithms for Robust Symmetric
Nonnegative Matrix Factorization,
SPLetters(25), No. 10, October 2018, pp. 1510-1514.
IEEE DOI
1810
iterative methods, matrix decomposition, optimisation,
polynomial matrices,
symmetric nonnegative matrix factorization (SNMF)
BibRef
Pang, J.,
Huang, J.,
Yang, X.,
Wang, Z.,
Yu, H.,
Huang, Q.,
Yin, B.,
Discovering Fine-Grained Spatial Pattern From Taxi Trips:
Where Point Process Meets Matrix Decomposition and Factorization,
ITS(19), No. 10, October 2018, pp. 3208-3219.
IEEE DOI
1810
Public transportation, Urban areas, Global Positioning System,
Matrix decomposition, Tools, Spatio-temporal pattern,
point process
BibRef
Huang, Z.W.[Zhi-Wu],
Wang, R.P.[Rui-Ping],
Li, X.Q.[Xian-Qiu],
Liu, W.X.[Wen-Xian],
Shan, S.G.[Shi-Guang],
Van Gool, L.J.[Luc J.],
Chen, X.L.[Xi-Lin],
Geometry-Aware Similarity Learning on SPD Manifolds for Visual
Recognition,
CirSysVideo(28), No. 10, October 2018, pp. 2513-2523.
IEEE DOI
1811
Symmetric Positive Definite matrices (SPD).
Manifolds, Measurement, Geometry, Optimization, Covariance matrices,
Symmetric matrices, Matrix decomposition,
PSD manifold
BibRef
Guan, N.Y.[Nai-Yang],
Liu, T.,
Zhang, Y.,
Tao, D.C.[Da-Cheng],
Davis, L.S.,
Truncated Cauchy Non-Negative Matrix Factorization,
PAMI(41), No. 1, January 2019, pp. 246-259.
IEEE DOI
1812
Face, Robustness, Matrix decomposition, Linear programming,
Programming, Sparse matrices, Analytical models,
half-quadratic programming
BibRef
Park, D.,
Kyrillidis, A.,
Caramanis, C.,
Sanghavi, S.,
Finding Low-Rank Solutions via Nonconvex Matrix Factorization,
Efficiently and Provably,
SIIMS(11), No. 4, 2018, pp. 2165-2204.
DOI Link
1901
BibRef
Zhang, W.K.[Wen-Kai],
Fu, K.[Kun],
Sun, X.[Xian],
Zhang, Y.H.[Yu-Hang],
Sun, H.[Hao],
Wang, H.Q.[Hong-Qi],
Joint optimisation convex-negative matrix factorisation for multi-modal
image collection summarisation based on images and tags,
IET-CV(13), No. 2, March 2019, pp. 125-130.
DOI Link
1902
BibRef
Fu, X.,
Huang, K.,
Sidiropoulos, N.D.,
Ma, W.,
Nonnegative Matrix Factorization for Signal and Data Analytics:
Identifiability, Algorithms, and Applications,
SPMag(36), No. 2, March 2019, pp. 59-80.
IEEE DOI
1903
matrix decomposition, NMF, nonnegativity constraints,
low-rank latent factor matrices, data matrix, data analytics,
Hyperspectral imaging
BibRef
Tichŭ, O.,
Bódiová, L.,
mídl, V.,
Bayesian Non-Negative Matrix Factorization With Adaptive Sparsity and
Smoothness Prior,
SPLetters(26), No. 3, March 2019, pp. 510-514.
IEEE DOI
1903
Bayes methods, covariance matrices,
expectation-maximisation algorithm, image sequences,
dynamic renal scintigraphy
BibRef
Kohjima, M.[Masahiro],
Matsubayashi, T.[Tatsushi],
Sawada, H.[Hiroshi],
Learning of Nonnegative Matrix Factorization Models for Inconsistent
Resolution Dataset Analysis,
IEICE(E102-D), No. 4, April 2019, pp. 715-723.
WWW Link.
1904
BibRef
Atif, S.M.[Syed Muhammad],
Qazi, S.[Sameer],
Gillis, N.[Nicolas],
Improved SVD-based initialization for nonnegative matrix
factorization using low-rank correction,
PRL(122), 2019, pp. 53-59.
Elsevier DOI
1904
Nonnegative matrix factorization, Initialization,
Singular value decomposition,
CR1-NMF
BibRef
Pan, J.J.[Jun-Jun],
Gillis, N.[Nicolas],
Generalized Separable Nonnegative Matrix Factorization,
PAMI(43), No. 5, May 2021, pp. 1546-1561.
IEEE DOI
2104
Matrix decomposition, Indexes, Hyperspectral imaging,
Source separation, Computational modeling, Data models, algorithms
BibRef
Gong, M.,
Jiang, X.,
Li, H.,
Tan, K.C.,
Multiobjective Sparse Non-Negative Matrix Factorization,
Cyber(49), No. 8, August 2019, pp. 2941-2954.
IEEE DOI
1905
Matrix decomposition, Pareto optimization, Sparse matrices,
Acceleration, Cybernetics, Semantics, Bias effects,
sparsity
BibRef
Vanegas, J.A.[Jorge A.],
Escalante, H.J.[Hugo Jair],
González, F.A.[Fabio A.],
Scalable multi-label annotation via semi-supervised kernel semantic
embedding,
PRL(123), 2019, pp. 97-103.
Elsevier DOI
1906
BibRef
Earlier:
Semi-supervised Online Kernel Semantic Embedding for Multi-label
Annotation,
CIARP17(693-701).
Springer DOI
1802
Semantic representation, Semi-supervised learning,
Learning on a budget, Kernel matrix factorization, Multi-label annotation
BibRef
Otálora-Montenegro, S.[Sebastian],
Pérez-Rubiano, S.A.[Santiago A.],
González, F.A.[Fabio A.],
Online Matrix Factorization for Space Embedding Multilabel Annotation,
CIARP13(I:343-350).
Springer DOI
1311
BibRef
Akyildiz, Ö.D.[Ömer Deniz],
Míguez, J.[Joaquín],
Dictionary filtering: a probabilistic approach to online matrix
factorisation,
SIViP(13), No. 4, June 2019, pp. 737-744.
WWW Link.
1906
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Kaloorazi, M.F.,
Chen, J.,
Randomized Truncated Pivoted QLP Factorization for Low-Rank Matrix
Recovery,
SPLetters(26), No. 7, July 2019, pp. 1075-1079.
IEEE DOI
1906
Matrix decomposition, Sparse matrices,
Signal processing algorithms, Approximation algorithms,
robust PCA
BibRef
Crannell, A.[Annalisa],
Frantz, M.[Marc],
Futamura, F.[Fumiko],
Factoring a Homography to Analyze Projective Distortion,
JMIV(61), No. 7, September 2019, pp. 967-989.
Springer DOI
1908
BibRef
Belachew, M.T.[Melisew Tefera],
Efficient algorithm for sparse symmetric nonnegative matrix
factorization,
PRL(125), 2019, pp. 735-741.
Elsevier DOI
1909
Sparse symmetric nonnegative matrix factorization,
Coordinate-descent method, Feature extraction, Sparsity
BibRef
Tosyali, A.[Ali],
Kim, J.H.[Jin-Ho],
Choi, J.[Jeongsub],
Jeong, M.K.[Myong K.],
Regularized asymmetric nonnegative matrix factorization for
clustering in directed networks,
PRL(125), 2019, pp. 750-757.
Elsevier DOI
1909
Clustering, Directed network, Nonnegative matrix factorization
BibRef
Pang, M.[Meng],
Cheung, Y.M.[Yiu-Ming],
Liu, R.S.[Ri-Sheng],
Lou, J.[Jian],
Lin, C.[Chuang],
Toward Efficient Image Representation:
Sparse Concept Discriminant Matrix Factorization,
CirSysVideo(29), No. 11, November 2019, pp. 3184-3198.
IEEE DOI
1911
Image reconstruction, Sparse matrices, Image representation,
Image coding, Optimization, Laplace equations, Data mining,
sparse coding
BibRef
Pang, M.[Meng],
Lin, C.[Chuang],
Liu, R.S.[Ri-Sheng],
Fan, X.[Xin],
Jiang, J.F.[Ji-Feng],
Luo, Z.X.[Zhong-Xuan],
Sparse concept discriminant matrix factorization for image
representation,
ICIP15(1255-1259)
IEEE DOI
1512
Sparse coding
BibRef
Yi, Y.G.[Yu-Gen],
Wang, J.Z.[Jian-Zhong],
Zhou, W.[Wei],
Zheng, C.X.[Cai-Xia],
Kong, J.[Jun],
Qiao, S.J.[Shao-Jie],
Non-Negative Matrix Factorization With Locality Constrained Adaptive
Graph,
CirSysVideo(30), No. 2, February 2020, pp. 427-441.
IEEE DOI
2002
Manifolds, Matrix decomposition, Clustering algorithms,
Linear programming, Dimensionality reduction, Task analysis,
locality constraint
BibRef
Yi, Y.G.[Yu-Gen],
Chen, Y.Q.[Yu-Qi],
Wang, J.Z.[Jian-Zhong],
Lei, G.[Gang],
Dai, J.Y.[Jiang-Yan],
Zhang, H.H.[Hui-Hui],
Joint feature representation and classification via adaptive graph
semi-supervised nonnegative matrix factorization,
SP:IC(89), 2020, pp. 115984.
Elsevier DOI
2010
Feature representation, Nonnegative matrix factorization,
Adaptive graph, Label propagation, Classification
BibRef
Yi, C.[Chen],
Zhao, Y.Q.[Yong-Qiang],
Chan, J.C.W.[Jonathan Cheung-Wai],
Kong, S.G.[Seong G.],
Joint Spatial-spectral Resolution Enhancement of Multispectral Images
with Spectral Matrix Factorization and Spatial Sparsity Constraints,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Teboulle, M.[Marc],
Vaisbourd, Y.[Yakov],
Novel Proximal Gradient Methods for Nonnegative Matrix Factorization
with Sparsity Constraints,
SIIMS(13), No. 1, 2020, pp. 381-421.
DOI Link
2004
BibRef
Xu, S.[Shuang],
Zhang, C.X.[Chun-Xia],
Zhang, J.S.[Jiang-She],
Adaptive quantile low-rank matrix factorization,
PR(103), 2020, pp. 107310.
Elsevier DOI
2005
Low-rank matrix factorization,
Mixture of asymmetric Laplace distributions, Skew noise
BibRef
Xiong, Y.J.[Ying-Jun],
Xu, Y.[Yan],
Shu, X.[Xin],
Cross-view hashing via supervised deep discrete matrix factorization,
PR(103), 2020, pp. 107270.
Elsevier DOI
2005
Matrix factorization, Cross-view hashing, Similarity search
BibRef
Pu, J.,
Panagakis, Y.,
Petridis, S.,
Shen, J.,
Pantic, M.,
Blind Audio-Visual Localization and Separation via Low-Rank and
Sparsity,
Cyber(50), No. 5, May 2020, pp. 2288-2301.
IEEE DOI
2005
Visualization, Feature extraction, Sparse matrices,
Matrix decomposition, Task analysis, Microphones, Spectrogram,
sparsity
BibRef
Haeffele, B.D.,
Vidal, R.,
Structured Low-Rank Matrix Factorization: Global Optimality,
Algorithms, and Applications,
PAMI(42), No. 6, June 2020, pp. 1468-1482.
IEEE DOI
2005
Optimization, Machine learning, Principal component analysis,
Videos, Standards, Calcium, Imaging, Low-rank matrix factorization,
hyperspectral compressed recovery
BibRef
Lane, C.,
Haeffele, B.D.,
Vidal, R.,
Adaptive Online k-Subspaces with Cooperative Re-Initialization,
RSL-CV19(678-688)
IEEE DOI
2004
gradient methods, optimisation, stochastic processes,
adaptive k-subspace formulation, synthetic image data, matrix factorization
BibRef
Gouvert, O.,
Oberlin, T.,
Févotte, C.,
Negative Binomial Matrix Factorization,
SPLetters(27), 2020, pp. 815-819.
IEEE DOI
2006
Collaborative filtering, majorization-minimization,
non-negative matrix factorization, over-dispersion, Poisson factorization
BibRef
Zhang, S.,
Soubies, E.,
Févotte, C.,
On the Identifiability of Transform Learning for Non-Negative Matrix
Factorization,
SPLetters(27), 2020, pp. 1555-1559.
IEEE DOI
2009
Source separation, Discrete cosine transforms,
Adaptation models, Linear programming,
joint diagonalization
BibRef
Xue, F.[Feng],
Wang, W.B.[Wen-Bo],
Zhou, W.J.[Wen-Jie],
Zeng, T.[Tao],
Yang, T.[Tian],
Cross-modal retrieval via label category supervised matrix
factorization hashing,
PRL(138), 2020, pp. 469-475.
Elsevier DOI
2010
Cross-modal retrieval, Matrix factorization, Hash
BibRef
Wu, J.,
Luo, F.,
Zhang, Y.,
Wang, H.,
Semi-discrete Matrix Factorization,
IEEE_Int_Sys(35), No. 5, September 2020, pp. 73-83.
IEEE DOI
2010
Binary codes, Optimization, Computational modeling,
Recommender systems, Quantization (signal), Intelligent systems,
Learning to Hash
BibRef
Peng, S.Y.[Si-Yuan],
Ser, W.[Wee],
Chen, B.D.[Ba-Dong],
Lin, Z.P.[Zhi-Ping],
Robust semi-supervised nonnegative matrix factorization for image
clustering,
PR(111), 2021, pp. 107683.
Elsevier DOI
2012
Nonnegative matrix factorization, Supervised information,
Correntropy, Outliers, Image clustering
BibRef
Yin, J.X.[Jing-Xing],
Peng, S.Y.[Si-Yuan],
Yang, Z.J.[Zhi-Jing],
Chen, B.D.[Ba-Dong],
Lin, Z.P.[Zhi-Ping],
Hypergraph based semi-supervised symmetric nonnegative matrix
factorization for image clustering,
PR(137), 2023, pp. 109274.
Elsevier DOI
2302
Symmetric nonnegative matrix factorization,
Hypergraph learning, Semi-supervised learning, Clustering
BibRef
Peng, S.Y.[Si-Yuan],
Yin, J.X.[Jing-Xing],
Yang, Z.J.[Zhi-Jing],
Chen, B.D.[Ba-Dong],
Lin, Z.P.[Zhi-Ping],
Multiview Clustering via Hypergraph Induced Semi-Supervised Symmetric
Nonnegative Matrix Factorization,
CirSysVideo(33), No. 10, October 2023, pp. 5510-5524.
IEEE DOI
2310
BibRef
Ma, J.Q.[Jia-Qi],
Zhang, Y.P.[Yi-Peng],
Zhang, L.F.[Le-Fei],
Discriminative subspace matrix factorization for multiview data
clustering,
PR(111), 2021, pp. 107676.
Elsevier DOI
2012
Dimension reduction, Multiview, Clustering, Machine learning
BibRef
Tian, M.,
Leng, C.,
Wu, H.,
Basu, A.,
Total Variation Constrained Graph-Regularized Convex Non-Negative
Matrix Factorization for Data Representation,
SPLetters(28), 2021, pp. 126-130.
IEEE DOI
2101
Signal processing algorithms, TV, Symmetric matrices,
Linear programming, Convergence, Sparse matrices, Robustness,
data representation
BibRef
Hedjam, R.[Rachid],
Abdesselam, A.[Abdelhamid],
Melgani, F.[Farid],
NMF with feature relationship preservation penalty term for
clustering problems,
PR(112), 2021, pp. 107814.
Elsevier DOI
2102
NMF, Orthogonal NMF, Clustering, Unsupervised learning,
Low-rank matrix factorization,
BibRef
Yang, B.,
Zhang, X.,
Nie, F.,
Wang, F.,
Yu, W.,
Wang, R.,
Fast Multi-View Clustering via Nonnegative and Orthogonal
Factorization,
IP(30), 2021, pp. 2575-2586.
IEEE DOI
2102
Clustering algorithms, Optimization, Matrix decomposition,
Acceleration, Sparse matrices, Computational efficiency,
nonnegative and orthogonal factorization (NOF)
BibRef
Zhang, C.H.[Chi-Hao],
Zhang, S.H.[Shi-Hua],
Bayesian Joint Matrix Decomposition for Data Integration with
Heterogeneous Noise,
PAMI(43), No. 4, April 2021, pp. 1184-1196.
IEEE DOI
2103
Matrix decomposition, Bayes methods, Data integration,
Inference algorithms, Data models, Data mining,
maximum a posterior
BibRef
Liu, S.[Shuai],
Feng, J.[Jie],
Tian, Z.Q.[Zhi-Qiang],
Variational Low-Rank Matrix Factorization with Multi-Patch
Collaborative Learning for Hyperspectral Imagery Mixed Denoising,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Zhao, Y.[Yang],
Wang, H.Y.[Hui-Yang],
Pei, J.H.[Ji-Hong],
Deep Non-Negative Matrix Factorization Architecture Based on
Underlying Basis Images Learning,
PAMI(43), No. 6, June 2021, pp. 1897-1913.
IEEE DOI
2106
Feature extraction, Linear programming, Image reconstruction,
Kernel, Sparse matrices, Convergence, Data analysis,
face recognition
BibRef
Zhao, Y.[Yang],
Deng, F.[Furong],
Pei, J.H.[Ji-Hong],
Yang, X.[Xuan],
Progressive Deep Non-Negative Matrix Factorization Architecture with
Graph Convolution-based Basis Image Reorganization,
PR(132), 2022, pp. 108984.
Elsevier DOI
2209
Deep non-negative matrix factorization, Graph convolution,
Basis image reconstruction, Basis image factorization, Face recognition
BibRef
Yang, Z.Y.[Zu-Yuan],
Liang, N.Y.[Nai-Yao],
Yan, W.[Wei],
Li, Z.N.[Zhen-Ni],
Xie, S.L.[Sheng-Li],
Uniform Distribution Non-Negative Matrix Factorization for Multiview
Clustering,
Cyber(51), No. 6, June 2021, pp. 3249-3262.
IEEE DOI
2106
Matrix decomposition, Computational modeling, Analytical models,
Manifolds, Data models, Convergence, Automation, Clustering,
non-negative matrix factorization (NMF)
BibRef
Zhang, Y.[Ying],
Li, X.L.[Xiang-Li],
Jia, M.X.[Meng-Xue],
Adaptive graph-based discriminative nonnegative matrix factorization
for image clustering,
SP:IC(95), 2021, pp. 116253.
Elsevier DOI
2106
Nonnegative matrix factorization,
Adaptive graph regularization, Semi-supervised learning
BibRef
Wu, W.H.[Wen-Hui],
Jia, Y.H.[Yu-Heng],
Wang, S.Q.[Shi-Qi],
Wang, R.[Ran],
Fan, H.F.[Hong-Fei],
Kwong, S.[Sam],
Positive and Negative Label-Driven Nonnegative Matrix Factorization,
CirSysVideo(31), No. 7, July 2021, pp. 2698-2710.
IEEE DOI
2107
Optimization, Task analysis, Manifolds, Data models,
Fans, Urban areas, negative label
BibRef
Wen, J.[Jie],
Yan, K.[Ke],
Zhang, Z.[Zheng],
Xu, Y.[Yong],
Wang, J.Q.[Jun-Qian],
Fei, L.[Lunke],
Zhang, B.[Bob],
Adaptive Graph Completion Based Incomplete Multi-View Clustering,
MultMed(23), 2021, pp. 2493-2504.
IEEE DOI
2108
Clustering methods, Machine learning,
Visualization, Task analysis, Optimization,
similarity graph
BibRef
Wen, J.[Jie],
Zhang, Z.[Zheng],
Xu, Y.[Yong],
Zhong, Z.F.[Zuo-Feng],
Incomplete Multi-view Clustering via Graph Regularized Matrix
Factorization,
CEFR-LCV18(IV:593-608).
Springer DOI
1905
BibRef
Cai, T.[Ting],
Tan, V.Y.F.[Vincent Y. F.],
Févotte, C.[Cédric],
Adversarially-Trained Nonnegative Matrix Factorization,
SPLetters(28), 2021, pp. 1415-1419.
IEEE DOI
2108
Optimization, Standards, Task analysis, Matrix decomposition,
Dictionaries, Training, Signal processing algorithms,
matrix completion
BibRef
Wang, W.[Wei],
Chen, F.Y.[Fei-Yu],
Ge, Y.X.[Yong-Xin],
Huang, S.[Sheng],
Zhang, X.H.[Xiao-Hong],
Yang, D.[Dan],
Discriminative deep semi-nonnegative matrix factorization network
with similarity maximization for unsupervised feature learning,
PRL(149), 2021, pp. 157-163.
Elsevier DOI
2108
Discriminativity, Deep semi-NMF network,
Similarity maximization, Feature learning
BibRef
Zhang, Y.[Yan],
Zhang, Z.[Zhao],
Wang, Y.[Yang],
Zhang, Z.[Zheng],
Zhang, L.[Li],
Yan, S.C.[Shui-Cheng],
Wang, M.[Meng],
Dual-Constrained Deep Semi-Supervised Coupled Factorization Network
with Enriched Prior,
IJCV(129), No. 12, December 2021, pp. 3233-3254.
Springer DOI
2111
BibRef
Zou, Z.Y.[Zhi-Yuan],
Liu, W.B.[Wei-Bin],
Xing, W.W.[Wei-Wei],
AdaNFF: A new method for adaptive nonnegative multi-feature fusion to
scene classification,
PR(123), 2022, pp. 108402.
Elsevier DOI
2112
Scene classification, Adaptive feature fusion,
Nonnegative matrix factorization, Feature fusion boosting
BibRef
Wang, Q.[Qi],
He, X.[Xiang],
Jiang, X.[Xu],
Li, X.L.[Xue-Long],
Robust Bi-Stochastic Graph Regularized Matrix Factorization for Data
Clustering,
PAMI(44), No. 1, January 2022, pp. 390-403.
IEEE DOI
2112
Robustness, Sparse matrices, Matrix decomposition,
Loss measurement, Task analysis, Manifolds, Tools, robustness
BibRef
Cai, H.Q.[Han-Qin],
Hamm, K.[Keaton],
Huang, L.X.[Long-Xiu],
Needell, D.[Deanna],
Robust CUR Decomposition: Theory and Imaging Applications,
SIIMS(14), No. 4, 2021, pp. 1472-1503.
DOI Link
2112
BibRef
Li, H.R.[Hui-Rong],
Gao, Y.L.[Yue-Lin],
Liu, J.M.[Jun-Min],
Zhang, J.S.[Jiang-She],
Li, C.[Chao],
Semi-supervised graph regularized nonnegative matrix factorization
with local coordinate for image representation,
SP:IC(102), 2022, pp. 116589.
Elsevier DOI
2202
Nonnegative matrix factorization, Graph regularization,
Semi-supervised learning, Local coordinate
BibRef
Xie, T.[Ting],
Zhang, H.[Hua],
Liu, R.H.[Rui-Hua],
Xiao, H.G.[Han-Guang],
Accelerated sparse nonnegative matrix factorization for unsupervised
feature learning,
PRL(156), 2022, pp. 46-52.
Elsevier DOI
2205
Nonnegative matrix factorization, Clustering, Sparse
BibRef
Feng, L.[Lei],
Huang, J.[Jun],
Shu, S.[Senlin],
An, B.[Bo],
Regularized Matrix Factorization for Multilabel Learning With Missing
Labels,
Cyber(52), No. 5, May 2022, pp. 3710-3721.
IEEE DOI
2206
Correlation, Matrix decomposition, Manifolds, Training,
Adaptation models, Nickel, Cybernetics, Latent factors,
regularized matrix factorization
BibRef
Sun, Y.F.[Yan-Feng],
Wang, J.[Jie],
Guo, J.P.[Ji-Peng],
Hu, Y.L.[Yong-Li],
Yin, B.C.[Bao-Cai],
Globality constrained adaptive graph regularized non-negative matrix
factorization for data representation,
IET-IPR(16), No. 10, 2022, pp. 2577-2592.
DOI Link
2207
BibRef
Guo, J.P.[Ji-Peng],
Yin, S.[Shuai],
Sun, Y.F.[Yan-Feng],
Hu, Y.L.[Yong-Li],
Double Manifolds Regularized Non-negative Matrix Factorization for
Data Representation,
ICPR21(901-906)
IEEE DOI
2105
Manifolds, Learning systems, Adaptation models,
Clustering algorithms, Iterative methods, Task analysis
BibRef
Guo, J.P.[Ji-Peng],
Sun, Y.F.[Yan-Feng],
Gao, J.B.[Jun-Bin],
Hu, Y.L.[Yong-Li],
Yin, B.C.[Bao-Cai],
Low Rank Representation on Product Grassmann Manifolds for Multi-view
Subspace Clustering,
ICPR21(907-914)
IEEE DOI
2105
Manifolds, Upper bound, Computational modeling, Minimization,
Data models, Matrix decomposition
BibRef
Gillis, N.[Nicolas],
Hien, L.T.K.[Le Thi Khanh],
Leplat, V.[Valentin],
Tan, V.Y.F.[Vincent Y. F.],
Distributionally Robust and Multi-Objective Nonnegative Matrix
Factorization,
PAMI(44), No. 8, August 2022, pp. 4052-4064.
IEEE DOI
2207
Linear programming, Optimization, Standards, Data models,
Minimization, Image reconstruction, Dimensionality reduction,
multiplicative updates
BibRef
Yuan, A.H.[Ai-Hong],
You, M.B.[Meng-Bo],
He, D.J.[Dong-Jian],
Li, X.L.[Xue-Long],
Convex Non-Negative Matrix Factorization With Adaptive Graph for
Unsupervised Feature Selection,
Cyber(52), No. 6, June 2022, pp. 5522-5534.
IEEE DOI
2207
Manifolds, Computational modeling, Task analysis, Encoding,
Analytical models, Optimization, Feature extraction,
unsupervised feature selection (UFS)
BibRef
You, M.B.[Meng-Bo],
Yuan, A.H.[Ai-Hong],
He, D.J.[Dong-Jian],
Li, X.L.[Xue-Long],
Unsupervised Feature Selection via Neural Networks and
Self-Expression with Adaptive Graph Constraint,
PR(135), 2023, pp. 109173.
Elsevier DOI
2212
Unsupervised feature selection, Manifold structure,
Adaptive graph constraint, Neural networks
BibRef
Zhang, R.[Rui],
Zhang, Y.X.[Yun-Xing],
Lu, C.J.[Cheng-Jun],
Li, X.L.[Xue-Long],
Unsupervised Graph Embedding via Adaptive Graph Learning,
PAMI(45), No. 4, April 2023, pp. 5329-5336.
IEEE DOI
2303
Laplace equations, Graph neural networks, Adaptation models,
Adaptive learning, Task analysis, Decoding, Topology,
graph autoencoder
BibRef
Jia, Y.H.[Yu-Heng],
Liu, H.[Hui],
Hou, J.H.[Jun-Hui],
Kwong, S.[Sam],
Zhang, Q.F.[Qing-Fu],
Self-Supervised Symmetric Nonnegative Matrix Factorization,
CirSysVideo(32), No. 7, July 2022, pp. 4526-4537.
IEEE DOI
2207
Matrix decomposition, Symmetric matrices, Optimization,
Clustering methods, Faces, Sensitivity, Dimensionality reduction, clustering
BibRef
Magron, P.[Paul],
Févotte, C.[Cédric],
A Majorization-Minimization Algorithm for Nonnegative Binary Matrix
Factorization,
SPLetters(29), 2022, pp. 1526-1530.
IEEE DOI
2208
Data models, Logistics, Computational modeling, Upper bound,
Principal component analysis, Estimation,
majorization-minimization
BibRef
Wang, D.[Di],
Han, S.W.[Song-Wei],
Wang, Q.[Quan],
He, L.[Lihuo],
Tian, Y.M.[Yu-Min],
Gao, X.B.[Xin-Bo],
Pseudo-Label Guided Collective Matrix Factorization for Multiview
Clustering,
Cyber(52), No. 9, September 2022, pp. 8681-8691.
IEEE DOI
2208
Clustering methods, Interviews, Iterative methods, Cybernetics,
Correlation, Manifolds, Computational efficiency,
pseudo-label
BibRef
Rahiche, A.[Abderrahmane],
Cheriet, M.[Mohamed],
Variational Bayesian Orthogonal Nonnegative Matrix Factorization Over
the Stiefel Manifold,
IP(31), 2022, pp. 5543-5558.
IEEE DOI
2209
Bayes methods, Probabilistic logic, Manifolds,
Matrix decomposition, Task analysis, Source separation,
von Mises-Fisher distribution
BibRef
de Handschutter, P.[Pierre],
Gillis, N.[Nicolas],
A consistent and flexible framework for deep matrix factorizations,
PR(134), 2023, pp. 109102.
Elsevier DOI
2212
Deep matrix factorization, Loss functions,
Constrained optimization, First-order methods, Hyperspectral unmixing
BibRef
Liu, X.L.[Xin-Ling],
Hou, J.Y.[Jing-Yao],
Wang, J.J.[Jian-Jun],
Robust Low-Rank Matrix Recovery Fusing Local-Smoothness,
SPLetters(29), 2022, pp. 2552-2556.
IEEE DOI
2301
Minimization, TV, Linear matrix inequalities, Sparse matrices,
Indexes, Hyperspectral imaging, Signal processing algorithms,
hyperspectral images
BibRef
Chavoshinejad, J.[Jovan],
Seyedi, S.A.[Seyed Amjad],
Akhlaghian-Tab, F.[Fardin],
Salahian, N.[Navid],
Self-supervised semi-supervised nonnegative matrix factorization for
data clustering,
PR(137), 2023, pp. 109282.
Elsevier DOI
2302
Nonnegative matrix factorization, Semi-supervised learning,
Self-supervised learning, Ensemble clustering
BibRef
Sun, X.[Xia],
Li, B.[Bo],
Sutcliffe, R.[Richard],
Gao, Z.[Zhizezhang],
Kang, W.Y.[Wen-Ying],
Feng, J.[Jun],
Wse-MF: A weighting-based student exercise matrix factorization model,
PR(138), 2023, pp. 109285.
Elsevier DOI
2303
Educational data mining, Personalized exercise prediction, Matrix factorization
BibRef
Hou, L.S.[Liang-Shao],
Chu, D.[Delin],
Liao, L.Z.[Li-Zhi],
A Progressive Hierarchical Alternating Least Squares Method for
Symmetric Nonnegative Matrix Factorization,
PAMI(45), No. 5, May 2023, pp. 5355-5369.
IEEE DOI
2304
Symmetric matrices, Convergence, Matrix decomposition,
Dimensionality reduction, Data mining, Minimization, Systematics,
clustering
BibRef
Wang, K.[Kaijie],
He, F.[Fan],
He, M.Z.[Ming-Zhen],
Huang, X.L.[Xiao-Lin],
Learning non-parametric kernel via matrix decomposition for logistic
regression,
PRL(171), 2023, pp. 177-183.
Elsevier DOI
2306
Non-parametric kernel, Indefinite kernel, Matrix decomposition,
Kernel logistic regression
BibRef
Giraud, M.[Maxence],
Itier, V.[Vincent],
Boyer, R.[Rémy],
Zniyed, Y.[Yassine],
de Almeida, A.L.F.[André L.F.],
Tucker Decomposition Based on a Tensor Train of Coupled and
Constrained CP Cores,
SPLetters(30), 2023, pp. 758-762.
IEEE DOI
2307
Tensors, Matrix decomposition, Signal processing algorithms,
Estimation, Singular value decomposition, Couplings, Costs, Tensor,
multilinear algebra
BibRef
Pan, J.J.[Jun-Jun],
Ng, M.K.[Michael K.],
Separable Quaternion Matrix Factorization for Polarization Images,
SIIMS(16), No. 3, 2023, pp. 1281-1307.
DOI Link
2309
BibRef
Zuo, H.L.[Hong-Liang],
Li, S.[Shuo],
Liang, C.[Cong],
Li, J.T.[Jun-Tao],
Auto-adjustable hypergraph regularized non-negative matrix
factorization for image clustering,
PR(145), 2024, pp. 109963.
Elsevier DOI
2311
Non-negative matrix factorization, Hypergraph regularization,
Robustness, Outlier
BibRef
Li, Y.[Yinan],
Wang, R.[Ruili],
Fang, Y.Q.[Yu-Qiang],
Sun, M.[Meng],
Luo, Z.K.[Zhang-Kai],
Alternating Direction Method of Multipliers for Convolutive
Non-Negative Matrix Factorization,
Cyber(53), No. 12, December 2023, pp. 7735-7748.
IEEE DOI
2312
BibRef
Sugahara, K.[Kai],
Okamoto, K.[Kazushi],
Hierarchical matrix factorization for interpretable collaborative
filtering,
PRL(180), 2024, pp. 99-106.
Elsevier DOI
2404
Recommender systems, Collaborative filtering,
Hierarchical matrix factorization, Interpretable recommendation
BibRef
Moayed, H.[Hojjat],
Mansoori, E.G.[Eghbal G.],
Deep and wide nonnegative matrix factorization with embedded
regularization,
PR(153), 2024, pp. 110530.
Elsevier DOI
2405
Feature extraction, Deep learning,
Nonnegative matrix factorization, Channel augmentation, Regularization
BibRef
Zhai, Z.[Zheng],
Chen, H.C.[Heng-Chao],
Sun, Q.[Qiang],
Quadratic Matrix Factorization With Applications to Manifold Learning,
PAMI(46), No. 9, September 2024, pp. 6384-6401.
IEEE DOI
2408
Manifold learning, Manifolds, Minimization, Convergence, Fitting,
Approximation algorithms, Task analysis,
quadratic matrix factorization
BibRef
Yang, X.J.[Xiao-Jun],
Zhu, T.[Tuoji],
Peng, S.Y.[Si-Yuan],
Nie, F.P.[Fei-Ping],
Lin, Z.P.[Zhi-Ping],
Semi-supervised pivotal-aware nonnegative matrix factorization with
label and pairwise constraint propagation for data clustering,
PR(157), 2025, pp. 110933.
Elsevier DOI
2409
Nonnegative matrix factorization, Semi-supervised learning,
Dual constraint propagation, Data clustering
BibRef
Bhavana, P.[Prasad],
Padmanabhan, V.[Vineet],
Temporal Matrix Factorization:
A polynomial approach to latent factor estimation,
PR(157), 2025, pp. 110905.
Elsevier DOI
2409
Temporal matrix factorization, Recommender systems,
Temporal latent factor estimation
BibRef
Wang, Q.S.[Qing-Song],
Cui, C.F.[Chun-Feng],
Han, D.R.[De-Ren],
A Momentum Accelerated Algorithm for ReLU-Based Nonlinear Matrix
Decomposition,
SPLetters(31), 2024, pp. 2865-2869.
IEEE DOI
2411
NLMD -- relates to neural nets.
Signal processing algorithms, Sparse matrices,
Matrix decomposition, Optimization, Neural networks, Minimization,
nonlinearity
BibRef
Cui, G.S.[Guo-Sheng],
Wu, D.[Dan],
Li, Y.[Ye],
Li, J.Z.[Jian-Zhong],
Layer-wise normalized deep incomplete multiview nonnegative matrix
factorization,
PR(158), 2025, pp. 111010.
Elsevier DOI Code:
WWW Link.
2411
Layer-wise normalization, Model stableness,
Incomplete multiview clustering, Hypergraph regularization
BibRef
Zhang, S.Y.[Stephen Y.],
A unified framework for non-negative matrix and tensor factorisations
with a smoothed Wasserstein loss,
TAG-CV21(4178-4186)
IEEE DOI
2112
Geometry, Tensors, Transportation,
Imaging, Transforms
BibRef
Zhao, H.[Huan],
She, X.L.[Xiao-Lin],
Wang, S.[Song],
Ma, K.[Kaili],
Fast Discrete Matrix Factorization Hashing for Large-scale Cross-modal
Retrieval,
MMMod21(I:24-36).
Springer DOI
2106
BibRef
Mukkamala, M.C.[Mahesh Chandra],
Westerkamp, F.[Felix],
Laude, E.[Emanuel],
Cremers, D.[Daniel],
Ochs, P.[Peter],
Bregman Proximal Gradient Algorithms for Deep Matrix Factorization,
SSVM21(204-215).
Springer DOI
2106
BibRef
Peng, C.[Chong],
Chen, C.L.[Cheng-Lizhao],
Kang, Z.[Zhao],
Li, J.B.[Jian-Bo],
Cheng, Q.A.[Qi-Ang],
RES-PCA: A Scalable Approach to Recovering Low-Rank Matrices,
CVPR19(7309-7317).
IEEE DOI
2002
BibRef
Zheng, H.,
Liang, Z.,
Tian, F.,
Ming, Z.,
NMF-Based Comprehensive Latent Factor Learning with Multiview Data,
ICIP19(489-493)
IEEE DOI
1910
Comprehensive, multiview learning, latent factor learning,
non-negative matrix factorization (NMF).
BibRef
Pan, J.,
Ng, M.K.,
Zhang, X.,
Structured Convex Optimization Method for Orthogonal Nonnegative
Matrix Factorization,
ICPR18(459-464)
IEEE DOI
1812
Numerical models, Clustering algorithms, Optimization, Convergence,
Eigenvalues and eigenfunctions, Matrix decomposition
BibRef
Hwang, S.J.,
Kim, H.J.,
Ravi, S.N.,
Collins, M.D.,
Tao, Z.,
Singh, V.,
Tensorize, Factorize and Regularize:
Robust Visual Relationship Learning,
CVPR18(1014-1023)
IEEE DOI
1812
Visualization, Task analysis, Semantics, Genomics, Bioinformatics, Training
BibRef
Giampouras, P.V.,
Rontogiannis, A.A.,
Koutroumbas, K.D.,
Robust PCA via Alternating Iteratively Reweighted Low-Rank Matrix
Factorization,
ICIP18(3383-3387)
IEEE DOI
1809
Principal component analysis, Robustness, Sparse matrices,
Minimization, Cost function, Imaging, robust PCA, low-rank,
matrix factorization
BibRef
An, S.,
Multi-Task Nonnegative Matrix Factorization,
ICIP18(2272-2275)
IEEE DOI
1809
Task analysis, Matrix decomposition, Kernel, Encoding,
Clustering algorithms, Videos, Feature extraction,
daily activity recognition
BibRef
Sun, Y.,
Liu, X.,
Liang, L.,
Retrain-free fully connected layer optimization using matrix
factorization,
ICIP17(3914-3918)
IEEE DOI
1803
Complexity theory, Graphics processing units, Hardware,
Matrix decomposition, Optimization, Surgery, Task analysis,
neural network optimization
BibRef
Tepper, M.[Mariano],
Sapiro, G.[Guillermo],
Nonnegative Matrix Underapproximation for Robust Multiple Model
Fitting,
CVPR17(655-663)
IEEE DOI
1711
Computational modeling, Data models, Meteorology,
Parametric statistics, Robustness
BibRef
Larsson, V.,
Olsson, C.,
Compact Matrix Factorization with Dependent Subspaces,
CVPR17(4361-4370)
IEEE DOI
1711
Adaptation models, Computational modeling,
Data models, Estimation, Matrix decomposition, Predictive, models
BibRef
Ithapu, V.K.,
Kondor, R.,
Johnson, S.C.,
Singh, V.,
The Incremental Multiresolution Matrix Factorization Algorithm,
CVPR17(692-701)
IEEE DOI
1711
Covariance matrices, Image resolution,
Multiresolution analysis, Sparse matrices, Symmetric matrices, Tools
BibRef
Bao, Y.Y.[Yan-Yan],
Liu, H.W.[Hong-Wei],
Nonmonotone projected Barzilai-Borwein method for compressed sensing,
ICIVC17(756-760)
IEEE DOI
1708
Ions, Optical sensors, Barzilai-Borwein stepsize,
compressed sensing, gradient projection, nonmonotone, line, search
BibRef
Kohjima, M.,
Matsubayashi, T.,
Sawada, H.,
Non-negative multiple matrix factorization with Euclidean and
Kullback-Leibler mixed divergences,
ICPR16(2515-2520)
IEEE DOI
1705
Euclidean distance, Linear programming, Measurement uncertainty,
Optimization, Proposals, Smart, phones
BibRef
Lan, C.,
Li, X.,
Deng, Y.,
Amand, J.S.,
Huan, J.,
A PAC bound for joint matrix completion based on Partially Collective
Matrix Factorization,
ICPR16(2628-2633)
IEEE DOI
1705
Indexes, Loading, Mathematical model,
Picture archiving and communication systems, Sparse matrices, Standards
BibRef
Tripodi, R.,
Vascon, S.,
Pelillo, M.,
Context aware nonnegative matrix factorization clustering,
ICPR16(1719-1724)
IEEE DOI
1705
Clustering algorithms, Feature extraction,
Game theory, Games, Mathematical model, Matrix, decomposition
BibRef
Lemaitre, F.,
Lacassagne, L.,
Batched Cholesky factorization for tiny matrices,
DASIP16(130-137)
IEEE DOI
1704
mathematics computing
BibRef
Luo, Q.,
Han, Z.[Zhi],
Chen, X.[Xi'ai],
Wang, Y.[Yao],
Meng, D.Y.[De-Yu],
Liang, D.,
Tang, Y.D.[Yan-Dong],
Tensor RPCA by Bayesian CP Factorization with Complex Noise,
ICCV17(5029-5038)
IEEE DOI
1802
Bayes methods, Gaussian noise, approximation theory,
matrix algebra, matrix decomposition,
Tensile stress
BibRef
Chen, X.[Xi'ai],
Han, Z.[Zhi],
Wang, Y.[Yao],
Zhao, Q.[Qian],
Meng, D.Y.[De-Yu],
Tang, Y.D.[Yan-Dong],
Robust Tensor Factorization with Unknown Noise,
CVPR16(5213-5221)
IEEE DOI
1612
BibRef
Meng, D.Y.[De-Yu],
de la Torre, F.[Fernando],
Robust Matrix Factorization with Unknown Noise,
ICCV13(1337-1344)
IEEE DOI
1403
BibRef
Bampis, C.G.,
Maragos, P.,
Bovik, A.C.,
Projective non-negative matrix factorization for unsupervised graph
clustering,
ICIP16(1255-1258)
IEEE DOI
1610
Convergence
BibRef
Hong, J.H.,
Fitzgibbon, A.,
Secrets of Matrix Factorization: Approximations, Numerics, Manifold
Optimization and Random Restarts,
ICCV15(4130-4138)
IEEE DOI
1602
Algorithm design and analysis
BibRef
Wang, T.C.[Tian-Chun],
Ye, T.Q.[Teng-Qi],
Gurrin, C.[Cathal],
Transfer Nonnegative Matrix Factorization for Image Representation,
MMMod16(II: 3-14).
Springer DOI
1601
BibRef
Wang, Z.F.[Zhen-Fan],
Kong, X.W.[Xiang-Wei],
Fu, H.Y.[Hai-Yan],
Li, M.[Ming],
Zhang, Y.J.[Yu-Jia],
Feature Extraction via Multi-View Non-Negative Matrix Factorization
with Local Graph Regularization,
ICIP15(3500-3504)
IEEE DOI
1512
Feature extraction
BibRef
Turkan, M.[Mehmet],
Alain, M.[Martin],
Thoreau, D.[Dominique],
Guillotel, P.[Philippe],
Guillemot, C.[Christine],
Epitomic image factorization via neighbor-embedding,
ICIP15(4141-4145)
IEEE DOI
1512
Epitome learning
BibRef
Páez-Torres, A.E.[Andrés Esteban],
González, F.A.[Fabio A.],
Online Kernel Matrix Factorization,
CIARP15(651-658).
Springer DOI
1511
BibRef
Beltrán, V.[Viviana],
Vanegas, J.A.[Jorge A.],
González, F.A.[Fabio A.],
Semi-supervised Dimensionality Reduction via Multimodal Matrix
Factorization,
CIARP15(676-682).
Springer DOI
1511
BibRef
Chen, P.X.[Pei-Xian],
Wang, N.Y.[Nai-Yan],
Zhang, N.L.[Nevin L.],
Yeung, D.Y.[Dit-Yan],
Bayesian adaptive matrix factorization with automatic model selection,
CVPR15(1284-1292)
IEEE DOI
1510
BibRef
Oskarsson, M.[Magnus],
Batstone, K.,
Astrom, K.[Kalle],
Trust No One: Low Rank Matrix Factorization Using Hierarchical RANSAC,
CVPR16(5820-5829)
IEEE DOI
1612
BibRef
Jiang, F.Y.[Fang-Yuan],
Oskarsson, M.[Magnus],
Astrom, K.[Kalle],
On the minimal problems of low-rank matrix factorization,
CVPR15(2549-2557)
IEEE DOI
1510
BibRef
Huang, S.[Sheng],
Elhoseiny, M.[Mohamed],
Elgammal, A.M.[Ahmed M.],
Yang, D.[Dan],
Improving non-negative matrix factorization via ranking its bases,
ICIP14(5951-5955)
IEEE DOI
1502
Algorithm design and analysis
BibRef
Zafeiriou, L.[Lazaros],
Nikitidis, S.[Symeon],
Zafeiriou, S.P.[Stefanos P.],
Pantic, M.[Maja],
Slow features nonnegative matrix factorization for temporal data
decomposition,
ICIP14(1430-1434)
IEEE DOI
1502
Algorithm design and analysis
See also Slow Feature Analysis for Human Action Recognition.
BibRef
Nourbakhsh, F.[Farshad],
Bulo, S.R.[Samuel Rota],
Pelillo, M.[Marcello],
A Matrix Factorization Approach to Graph Compression,
ICPR14(76-81)
IEEE DOI
1412
Accuracy
BibRef
Chaudhari, S.[Sneha],
Murty, M.N.[M.Narasimha],
Average Overlap for Clustering Incomplete Data Using Symmetric
Non-negative Matrix Factorization,
ICPR14(1431-1436)
IEEE DOI
1412
Accuracy
BibRef
Zen, G.[Gloria],
Ricci, E.[Elisa],
Sebe, N.[Nicu],
Simultaneous Ground Metric Learning and Matrix Factorization with
Earth Mover's Distance,
ICPR14(3690-3695)
IEEE DOI
1412
Earth
BibRef
Shu, X.B.[Xian-Biao],
Porikli, F.M.[Fatih M.],
Ahuja, N.[Narendra],
Robust Orthonormal Subspace Learning:
Efficient Recovery of Corrupted Low-Rank Matrices,
CVPR14(3874-3881)
IEEE DOI
1409
BibRef
Li, Y.M.[Ying-Ming],
Yang, M.[Ming],
Zhang, Z.F.[Zhong-Fei],
Coordinate Ranking Regularized Non-negative Matrix Factorization,
ACPR13(215-219)
IEEE DOI
1408
data mining
BibRef
Qin, Z.[Zhen],
van Beek, P.[Peter],
Chen, X.[Xu],
Direct Matrix Factorization and Alignment Refinement: Application to
Defect Detection,
CRV14(135-142)
IEEE DOI
1406
Accuracy
BibRef
Guo, W.W.[Wei-Wei],
Hu, W.D.[Wei-Dong],
Boulgouris, N.V.[Nikolaos V.],
Patras, I.[Ioannis],
Semi-supervised visual recognition with constrained graph regularized
non negative matrix factorization,
ICIP13(2743-2747)
IEEE DOI
1402
Non Negative Matrix Factorization
BibRef
Liu, L.[Lei],
Comar, P.M.[Prakash Mandayam],
Saha, S.[Sabyasachi],
Tan, P.N.[Pang-Ning],
Nucci, A.[Antonio],
Recursive NMF: Efficient label tree learning for large multi-class
problems,
ICPR12(2148-2151).
WWW Link.
1302
non-negative matrix factorization
BibRef
Xie, S.N.[Sai-Ning],
Lu, H.T.[Hong-Tao],
He, Y.C.[Yang-Cheng],
Multi-task co-clustering via nonnegative matrix factorization,
ICPR12(2954-2958).
WWW Link.
1302
BibRef
Wang, N.Y.[Nai-Yan],
Yeung, D.Y.[Dit-Yan],
Bayesian Robust Matrix Factorization for Image and Video Processing,
ICCV13(1785-1792)
IEEE DOI
1403
BibRef
Wang, N.Y.[Nai-Yan],
Yao, T.S.[Tian-Sheng],
Wang, J.D.[Jing-Dong],
Yeung, D.Y.[Dit-Yan],
A Probabilistic Approach to Robust Matrix Factorization,
ECCV12(VII: 126-139).
Springer DOI
1210
BibRef
Zdunek, R.[Rafal],
Trust-Region Algorithm for Nonnegative Matrix Factorization with Alpha-
and Beta-Divergences,
DAGM12(226-235).
Springer DOI
1209
BibRef
Wang, D.[Dong],
Lu, H.C.[Hu-Chuan],
Incremental orthogonal projective non-negative matrix factorization and
its applications,
ICIP11(2077-2080).
IEEE DOI
1201
BibRef
Kumar, V.B.G.[Vijay B.G.],
Patras, I.[Ioannis],
Kotsia, I.[Irene],
Max-Margin Semi-NMF,
BMVC11(xx-yy).
HTML Version.
1110
Non-Negative Matrix Factorization
BibRef
Gupta, M.D.[Mithun Das],
Xiao, J.[Jing],
Non-negative matrix factorization as a feature selection tool for
maximum margin classifiers,
CVPR11(2841-2848).
IEEE DOI
1106
BibRef
Kirbiz, S.[Serap],
Cemgil, A.T.[A. Taylan],
Gunsel, B.[Bilge],
Bayesian Inference for Nonnegative Matrix Factor Deconvolution Models,
ICPR10(2812-2815).
IEEE DOI
1008
BibRef
Jammalamadaka, A.[Aruna],
Joshi, S.[Swapna],
Karthikeyan, S.,
Manjunath, B.S.,
Discriminative Basis Selection Using Non-negative Matrix Factorization,
ICPR10(1533-1536).
IEEE DOI
1008
BibRef
Karthikeyan, S.,
Joshi, S.[Swapna],
Manjunath, B.S.,
Grafton, S.[Scott],
Intra-class multi-output regression based subspace analysis,
ICIP12(1173-1176).
IEEE DOI
1302
See also Probabilistic subspace-based learning of shape dynamics modes for multi-view action recognition.
BibRef
Vadivel, K.S.[Karthikeyan Shanmuga],
Sargin, M.E.[Mehmet Emre],
Joshi, S.[Swapna],
Manjunath, B.S.,
Grafton, S.[Scott],
Generalized subspace based high dimensional density estimation,
ICIP11(1849-1852).
IEEE DOI
1201
BibRef
Joshi, S.[Swapna],
Karthikeyan, S.,
Manjunath, B.S.,
Grafton, S.[Scott],
Kiehl, K.A.[Kent A.],
Anatomical parts-based regression using non-negative matrix
factorization,
CVPR10(2863-2870).
IEEE DOI
1006
BibRef
Gu, Q.Q.[Quan-Quan],
Zhou, J.[Jie],
Two Dimensional Nonnegative Matrix Factorization,
ICIP09(2069-2072).
IEEE DOI
0911
BibRef
And:
Neighborhood Preserving Nonnegative Matrix Factorization,
BMVC09(xx-yy).
PDF File.
0909
BibRef
Gu, Q.Q.[Quan-Quan],
Zhou, J.[Jie],
Multiple Kernel Maximum Margin Criterion,
ICIP09(2049-2052).
IEEE DOI
0911
BibRef
Tang, J.[Jiayu],
Lewis, P.H.[Paul H.],
Non-negative matrix factorisation for object class discovery and image
auto-annotation,
CIVR08(105-112).
0807
BibRef
Earlier:
Using multiple segmentations for image auto-annotation,
CIVR07(581-586).
DOI Link
0707
BibRef
Li, L.[Le],
Zhang, Y.J.[Yu-Jin],
FastNMF: A fast monotonic fixed-point non-negative Matrix Factorization
algorithm with high ease of use,
ICPR08(1-4).
IEEE DOI
0812
BibRef
Rodrigues, J.J.[Jose J.],
Aguiar, P.M.Q.[Pedro M.Q.],
Xavier, J.M.F.[Joao M.F.],
ANSIG: An analytic signature for permutation-invariant two-dimensional
shape representation,
CVPR08(1-8).
IEEE DOI
0806
BibRef
Aguiar, P.M.Q.[Pedro M.Q.],
Xavier, J.M.F.[Joao M.F.],
Stosic, M.[Marko],
Spectrally optimal factorization of incomplete matrices,
CVPR08(1-8).
IEEE DOI
0806
BibRef
And:
Globally optimal solution to exploit rigidity when recovering structure
from motion under occlusion,
ICIP08(197-200).
IEEE DOI
0810
BibRef
Aguiar, P.M.Q.[Pedro M.Q.],
Miranda, A.R.[António R.],
de Castro, N.[Nuno],
Occlusion-Based Accurate Silhouettes from Video Streams,
ICIAR06(I: 816-826).
Springer DOI
0610
BibRef
Aguiar, P.M.Q.[Pedro M.Q.],
Moura, J.M.F.[José M.F.],
Joint Segmentation of Moving Object and Estimation of Background in
Low-Light Video using Relaxation,
ICIP07(V: 53-56).
IEEE DOI
0709
BibRef
Earlier:
Maximum Likelihood Estimation of the Template of a Rigid Moving Object,
EMMCVPR01(34-49).
Springer DOI
0205
BibRef
Earlier:
Detecting and Solving Template Ambiguities in Motion Segmentation,
ICIP97(II: 494-497).
IEEE DOI
BibRef
Earlier:
Incremental Motion Segmentation in Low Texture,
ICIP96(I: 233-236).
IEEE DOI
BibRef
Potluru, V.K.[Vamsi K.],
Plis, S.M.[Sergey M.],
Calhoun, V.D.[Vince D.],
Sparse shift-invariant NMF,
Southwest08(69-72).
IEEE DOI
0803
Non-negative Matrix Factorization.
BibRef
Zheng, W.S.[Wei-Shi],
Li, S.Z.[Stan Z.],
Lai, J.H.,
Liao, S.C.[Sheng-Cai],
On Constrained Sparse Matrix Factorization,
ICCV07(1-8).
IEEE DOI
0710
BibRef
Loke, Y.R.,
Ranganath, S.,
Batch Algorithm with Additional Shape Constraints for Non-Rigid
Factorization,
BMVC07(xx-yy).
PDF File.
0709
BibRef
Kim, Y.D.[Yong-Deok],
Choi, S.J.[Seung-Jin],
Nonnegative Tucker Decomposition,
ComponentAnalysis07(1-8).
IEEE DOI
0706
Tensor factorization.
Multilinear extension of matrix factorization.
BibRef
Samko, O.[Oksana],
Rosin, P.L.[Paul L.],
Marshall, A.D.[A. Dave],
Robust Automatic Data Decomposition Using a Modified Sparse NMF,
MIRAGE07(225-234).
Springer DOI
0703
Representation from real world data with unknown structure.
Non-negative matrix factorization (sparse NMF).
BibRef
Yuan, Z.J.[Zhi-Jian],
Oja, E.[Erkki],
Projective Nonnegative Matrix Factorization for Image Compression and
Feature Extraction,
SCIA05(333-342).
Springer DOI
0506
BibRef
Buchanan, A.M.,
Fitzgibbon, A.W.,
Damped Newton Algorithms for Matrix Factorization with Missing Data,
CVPR05(II: 316-322).
IEEE DOI
0507
BibRef
Aanĉs, H.[Henrik],
Fisker, R.[Rune],
Ċström, K.[Kalle],
Carstensen, J.M.[Jens Michael],
Factorization with Erroneous Data,
PCV02(A: 15).
0305
BibRef
Rother, C.,
Carlsson, S.,
Tell, D.,
Projective factorization of planes and cameras in multiple views,
ICPR02(II: 737-740).
IEEE DOI
0211
BibRef
Triggs, B.[Bill],
Plane + Parallax, Tensors, and Factorization,
ECCV00(I: 522-538).
Springer DOI
0003
BibRef
Aguiar, P.,
Weighted Factorization,
ICIP00(Vol I: 549-552).
IEEE DOI
0008
BibRef
Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Matrix Completion Algorithms .