13.3.12.8 Computational Complexity Issues, Computation

Miller, R.E., and Thather, J.W., (Eds.),
Complexity of Computer Computation,
Indexed as CCComp1972. BibRef 7200

Boult, T.E.,
Optimal Algorithms: Tools for Mathematical Modeling,
Complexity(3), 1987, pp. 183-200. BibRef 8700
And:
Using Optimal Algorithms to Test Model Assumptions in Computer Vision,
DARPA87(921-926). BibRef

Boult, T.E.,
What is Regular in Regularization?,
ICCV87(457-462). A look at regularization and some alternatives. BibRef 8700

Perlovsky, L.I.,
Conundrum of Combinatorial Complexity,
PAMI(20), No. 6, June 1998, pp. 666-670.
IEEE DOI 9807
BibRef

Falelakis, M., Diou, C., Delopoulos, A.,
Semantic Identification: Balancing between Complexity and Validity,
JASP(2006), No. 1, January 2006, pp. 1-12.
WWW Link. 0603
BibRef

Prusa, D.[Daniel], Werner, T.[Toma],
Universality of the Local Marginal Polytope,
PAMI(37), No. 4, April 2015, pp. 898-904.
IEEE DOI 1503
BibRef
Earlier: CVPR13(1738-1743)
IEEE DOI 1309
Complexity theory. min-sum problem, energy minimization. BibRef

Marangoni-Simonsen, D., Xie, Y.[Yao],
Sequential Changepoint Approach for Online Community Detection,
SPLetters(22), No. 8, August 2015, pp. 1035-1039.
IEEE DOI 1502
computational complexity BibRef

Liang, S., Luo, J., Liu, W., Wei, Y.,
Sketch Matching on Topology Product Graph,
PAMI(37), No. 8, August 2015, pp. 1723-1729.
IEEE DOI 1507
Complexity theory BibRef

Yin, H.B., Yang, E., Yu, X., Xia, Z.,
Fast Soft Decision Quantization With Adaptive Preselection and Dynamic Trellis Graph,
CirSysVideo(25), No. 8, August 2015, pp. 1362-1375.
IEEE DOI 1508
Complexity theory BibRef

Humeau-Heurtier, A.[Anne], Wu, C.W.[Chiu-Wen], Wu, S.D.[Shuen-De],
Refined Composite Multiscale Permutation Entropy to Overcome Multiscale Permutation Entropy Length Dependence,
SPLetters(22), No. 12, December 2015, pp. 2364-2367.
IEEE DOI 1512
computational complexity BibRef

Azami, H.[Hamed], Escudero, J., Humeau-Heurtier, A.[Anne],
Bidimensional Distribution Entropy to Analyze the Irregularity of Small-Sized Textures,
SPLetters(24), No. 9, September 2017, pp. 1338-1342.
IEEE DOI 1708
Algorithm design and analysis, Databases, Entropy, Surface texture, Surface treatment, Bidimensional dispersion entropy, irregularity, texture analysis, two-dimensional, BibRef

Azami, H.[Hamed], Virgilio da Silva, L.E.[Luiz Eduardo], Omoto, A.C.M.[Ana Carolina Mieko], Humeau-Heurtier, A.[Anne],
Two-dimensional dispersion entropy: An information-theoretic method for irregularity analysis of images,
SP:IC(75), 2019, pp. 178-187.
Elsevier DOI 1906
Biomedical image processing, Texture analysis, Irregularity, Two-dimensional dispersion entropy, Two-dimensional sample entropy BibRef

McEwen, J.D., Buttner, M., Leistedt, B., Peiris, H.V., Wiaux, Y.,
A Novel Sampling Theorem on the Rotation Group,
SPLetters(22), No. 12, December 2015, pp. 2425-2429.
IEEE DOI 1512
computational complexity BibRef

Ewert, W., Dembski, W.A., Marks, R.J.,
Measuring Meaningful Information in Images: Algorithmic Specified Complexity,
IET-CV(9), No. 6, 2015, pp. 884-894.
DOI Link 1512
computational complexity BibRef

Zhang, D., Matthé, M., Mendes, L.L., Fettweis, G.,
Message Passing Algorithms for Upper and Lower Bounding the Coded Modulation Capacity in a Large-Scale Linear System,
SPLetters(23), No. 4, April 2016, pp. 537-540.
IEEE DOI 1604
Complexity theory BibRef

Schoenecker, S., Luginbuhl, T.,
Characteristic Functions of the Product of Two Gaussian Random Variables and the Product of a Gaussian and a Gamma Random Variable,
SPLetters(23), No. 5, May 2016, pp. 644-647.
IEEE DOI 1604
Convolution BibRef

Ocegueda, O.[Omar], Dalmau, O.[Oscar], Garyfallidis, E.[Eleftherios], Descoteaux, M.[Maxime], Rivera, M.[Mariano],
On the computation of integrals over fixed-size rectangles of arbitrary dimension,
PRL(79), No. 1, 2016, pp. 68-72.
Elsevier DOI 1608
Integral Image BibRef

Aspelmeier, T.[Timo], Charitha, C., Luke, D.R.[D. Russell],
Local Linear Convergence of the ADMM/Douglas-Rachford Algorithms without Strong Convexity and Application to Statistical Imaging,
SIIMS(9), No. 2, 2016, pp. 842-868.
DOI Link 1608
BibRef

Weickert, J.[Joachim], Grewenig, S.[Sven], Schroers, C.[Christopher], Bruhn, A.[Andrés],
Cyclic Schemes for PDE-Based Image Analysis,
IJCV(118), No. 3, July 2016, pp. 275-299.
Springer DOI 1608
Efficient algorithms for PDEs in computer vision. Diffusion, optimization. BibRef

Chi, Y., Lu, Y.M.,
Kaczmarz Method for Solving Quadratic Equations,
SPLetters(23), No. 9, September 2016, pp. 1183-1187.
IEEE DOI 1609
Gaussian processes BibRef

Maya, J.A., Vega, L.R., Galarza, C.G.,
A Closed-Form Approximation for the CDF of the Sum of Independent Random Variables,
SPLetters(24), No. 1, January 2017, pp. 121-125.
IEEE DOI 1702
approximation theory BibRef

El Moataz, A.[Abderrahim], Lozes, F.[François], Toutain, M.[Matthieu],
Nonlocal PDEs on Graphs: From Tug-of-War Games to Unified Interpolation on Images and Point Clouds,
JMIV(57), No. 3, March 2017, pp. 381-401.
Springer DOI 1702
BibRef

Masiero, B.[Bruno], Nascimento, V.H.[Vítor H.],
Revisiting the Kronecker Array Transform,
SPLetters(24), No. 5, May 2017, pp. 525-529.
IEEE DOI 1704
array signal processing. Calculation of a matrix-vector product. BibRef

Jiao, Y.L.[Yu-Ling], Jin, B.[Bangti], Lu, X.L.[Xi-Liang],
Iterative Soft/Hard Thresholding With Homotopy Continuation for Sparse Recovery,
SPLetters(24), No. 6, June 2017, pp. 784-788.
IEEE DOI 1705
Continuation, convergence, iterative soft/hard thresholding (IST/IHT), solution, path BibRef

Cui, G., Fu, Y., Yu, X., Li, J.,
Local Ambiguity Function Shaping via Unimodular Sequence Design,
SPLetters(24), No. 7, July 2017, pp. 977-981.
IEEE DOI 1706
computational complexity, gradient methods, optimisation, radar detection, AISO algorithm, WISL, accelerated iterative sequential optimization algorithm, computational complexity, gradient method, high-speed target detection, local ambiguity function shaping, radar system, range bins, specific Doppler bins, unimodular sequence design, weighted integrated sidelobe level, Accelerated iterative sequential optimization (AISO), local ambiguity function, unimodular, sequence BibRef

Pyatkin, A.[Artem], Aloise, D.[Daniel], Mladenovic, N.[Nenad],
NP-Hardness of balanced minimum sum-of-squares clustering,
PRL(97), No. 1, 2017, pp. 44-45.
Elsevier DOI 1709
Balanced clustering BibRef

Pustelnik, N.[Nelly], Condat, L.[Laurent],
Proximity Operator of a Sum of Functions; Application to Depth Map Estimation,
SPLetters(24), No. 12, December 2017, pp. 1827-1831.
IEEE DOI 1712
convex programming, graph theory, image processing, optimisation, convex optimization, depth map estimation, image processing, support function BibRef

Yadav, D.K.[Devendra Kumar], Kuldeep, G.[Gajraj], Joshi, S.D.,
Ramanujan Sums as Derivatives and Applications,
SPLetters(25), No. 3, March 2018, pp. 413-416.
IEEE DOI 1802
Estimation, Image edge detection, Kernel, Noise level, Presses, Signal processing, Discrete fourier transform, BibRef

Radhika, S., Sivabalan, A.,
ZA-APA with zero attractor controller selection criterion for sparse system identification,
SIViP(12), No. 2, February 2018, pp. 371-377.
Springer DOI 1802
BibRef

Bergmann, R.[Ronny], Tenbrinck, D.[Daniel],
A Graph Framework for Manifold-Valued Data,
SIIMS(11), No. 1, 2018, pp. 325-360.
DOI Link 1804
BibRef

Sun, C.[Chao], Su, Y.[Yao], Yu, X.G.[Xin-Guo],
Machine Solving on Hypergeometric Distribution Problems,
PSIVTWS17(102-115).
Springer DOI 1806
BibRef

Heravi, A.R., Hodtani, G.A.,
A New Information Theoretic Relation Between Minimum Error Entropy and Maximum Correntropy,
SPLetters(25), No. 7, July 2018, pp. 921-925.
IEEE DOI 1807
entropy, information theory, minimum entropy methods, statistical analysis, MCC, MEE, information theoretic learning, minimum error entropy BibRef

Wang, Z., Lin, J., Wang, Z.,
Hardware-Oriented Compression of Long Short-Term Memory for Efficient Inference,
SPLetters(25), No. 7, July 2018, pp. 984-988.
IEEE DOI 1807
computational complexity, data compression, embedded systems, matrix multiplication, recurrent neural nets, sparse matrices, recurrent neural networks (RNNs) BibRef

Khanna, S.[Saurabh], Murthy, C.R.[Chandra Ramabhadra],
Sparse Recovery From Multiple Measurement Vectors Using Exponentiated Gradient Updates,
SPLetters(25), No. 10, October 2018, pp. 1485-1489.
IEEE DOI 1810
convex programming, iterative methods, sparse matrices, vectors, multiple measurement vector support recovery algorithms, Von Neumann divergence BibRef

Wang, H., Yuan, J.,
Representative Selection on a Hypersphere,
SPLetters(25), No. 11, November 2018, pp. 1660-1664.
IEEE DOI 1811
computational complexity, computational geometry, data analysis, gradient methods, representative examples, pattern discovery, representative selection BibRef

Wang, Y., Tian, Z.,
IVDST: A Fast Algorithm for Atomic Norm Minimization in Line Spectral Estimation,
SPLetters(25), No. 11, November 2018, pp. 1715-1719.
IEEE DOI 1811
compressed sensing, computational complexity, concave programming, convex programming, gradient methods, shrinkage thresholding BibRef

Chen, J.[Jian], He, M.[Minfan], Zeng, T.[Taishan],
A multiscale Galerkin method for second-order boundary value problems of Fredholm integro-differential equation II: Efficient algorithm for the discrete linear system,
JVCIR(58), 2019, pp. 112-118.
Elsevier DOI 1901
Multiscale Galerkin method (MGM), Multilevel augmentation method (MAM), Fredholm integro-differential equation BibRef

Mello, L.H.S.[Lucas Henrique Sousa], Varejão, F.M.[Flávio M.], Rodrigues, A.L.[Alexandre L.], Rauber, T.W.[Thomas W.],
NP-Hardness of minimum expected coverage,
PRL(117), 2019, pp. 45-51.
Elsevier DOI 1901
Complexity, Multi-label learning, Loss minimization, Coverage BibRef

Mazo, L.[Loïc],
Multi-scale Arithmetization of Linear Transformations,
JMIV(61), No. 4, May 2019, pp. 432-442.
Springer DOI 1904
BibRef

Farzmahdi, M.[Mojtaba], Luo, R.[Rong],
Exact window memoization: an optimization method for high-performance image processing,
RealTimeIP(16), No. 2, April 2019, pp. 491-503.
Springer DOI 1904
Efficent computation, using data redundancy to minimize redundant computations. BibRef

Yang, J., Lin, J., Shi, Q., Li, Q.,
An ADMM-Based Approach to Robust Array Pattern Synthesis,
SPLetters(26), No. 6, June 2019, pp. 898-902.
IEEE DOI 1906
array signal processing, convex programming, minimax techniques, ADMM-based approach, bounded-sphere model, alternating direction method of multipliers (ADMM) BibRef

Kushinsky, Y., Maron, H., Dym, N., Lipman, Y.,
Sinkhorn Algorithm for Lifted Assignment Problems,
SIIMS(12), No. 2, 2019, pp. 716-735.
DOI Link 1907
solving linear programs emerging from optimal transport BibRef

Lebrat, L.[Léo], de Gournay, F.[Frédéric], Kahn, J.[Jonas], Weiss, P.[Pierre],
Optimal Transport Approximation of 2-Dimensional Measures,
SIIMS(12), No. 2, 2019, pp. 762-787.
DOI Link 1907
Applications in advanced sampling theory, nonphotorealistic rendering, and path planning. BibRef

Hernandez, M.,
A Comparative Study of Different Variants of Newton-Krylov PDE-Constrained Stokes-LDDMM Parameterized in the Space of Band-Limited Vector Fields,
SIIMS(12), No. 2, 2019, pp. 1038-1070.
DOI Link 1907
BibRef

Debarnot, V.[Valentin], Kahn, J.[Jonas], Weiss, P.[Pierre],
Multiview Attenuation Estimation and Correction,
JMIV(61), No. 6, July 2019, pp. 780-797.
Springer DOI 1907
Used in X-ray or optical tomography and lidar. BibRef

Zhang, H., Wei, X., Wang, R., Meng, F.,
An Efficient Base Conversion Using Variable Length Segmentation and Remainder Transfer,
SPLetters(26), No. 8, August 2019, pp. 1227-1231.
IEEE DOI 1908
digital arithmetic, optimisation, transfer functions, variable length segmentation, conversion overflows, remainder transfer function BibRef

Dytso, A.[Alex], Cardone, M.[Martina], Poor, H.V.[H. Vincent],
On Estimating the Norm of a Gaussian Vector Under Additive White Gaussian Noise,
SPLetters(26), No. 9, September 2019, pp. 1325-1329.
IEEE DOI 1909
AWGN, estimation theory, least mean squares methods, signal processing, vectors, Gaussian vector norm estimation, Gaussian noise BibRef

Abeida, H., Delmas, J.,
Slepian-Bangs Formula and Cramér-Rao Bound for Circular and Non-Circular Complex Elliptical Symmetric Distributions,
SPLetters(26), No. 10, October 2019, pp. 1561-1565.
IEEE DOI 1909
Gaussian distribution, Stochastic processes, Noise measurement, Electronic countermeasures, Closed-form solutions, non-circular complex elliptical symmetric distributions BibRef

Rabanser, S.[Simon], Neumann, L.[Lukas], Haltmeier, M.[Markus],
Analysis of the Block Coordinate Descent Method for Linear Ill-Posed Problems,
SIIMS(12), No. 4, 2019, pp. 1808-1832.
DOI Link 1912
BibRef

Reinhard, E., Garces, E., Stauder, J.,
Repeated Look-Up Tables,
IP(29), 2020, pp. 2370-2379.
IEEE DOI 2001
Table lookup, Optimization, Interpolation, Dynamic range, Hardware, Decoding, Standards, Look-up tables BibRef

Shen, B., Yang, Y., Zhou, Z., Fan, P., Guan, Y.,
New Optimal Binary Z-Complementary Pairs of Odd Length 2^m+3,
SPLetters(26), No. 12, December 2019, pp. 1931-1934.
IEEE DOI 2001
Iterative methods, Correlation, Zero correlation zone, Interference, Boolean functions, Aperiodic correlation, Z-complementary pair (ZCP) BibRef

Adhikary, A.R., Sarkar, P., Majhi, S.,
A Direct Construction of Q-Ary Even Length Z-Complementary Pairs Using Generalized Boolean Functions,
SPLetters(27), 2020, pp. 146-150.
IEEE DOI 2001
Even-length binary Z-complementary pairs (EB-ZCPs), Generalized Boolean functions (GBFs), Z-complementary pair (ZCP) BibRef

Ghosh, G.[Gobinda], Majhi, S.[Sudhan], Sarkar, P.[Palash], Upadhaya, A.K.[Ashish Kumar],
Direct Construction of Optimal Z-Complementary Code Sets with Even Lengths by Using Generalized Boolean Functions,
SPLetters(29), No. 2022, pp. 872-876.
IEEE DOI 2204
Multicarrier code division multiple access, Boolean functions, OFDM, Zero correlation zone, Interference, Telecommunications, ZCZ BibRef

Sarkar, P.[Palash], Majhi, S.[Sudhan], Liu, Z.L.[Zi-Long],
Pseudo-Boolean Functions for Optimal Z-Complementary Code Sets With Flexible Lengths,
SPLetters(28), 2021, pp. 1350-1354.
IEEE DOI 2107
Multicarrier code division multiple access, Boolean functions, Upper bound, Correlation, Transforms, zero correlation zone (ZCZ) BibRef

Xue, D., DeBrunner, L.S., DeBrunner, V.,
Linear Convolution Filter to Reduce Computational Complexity Based on Discrete Hirschman Transform,
SPLetters(26), No. 12, December 2019, pp. 1935-1939.
IEEE DOI 2001
Convolution, Computational complexity, Discrete Fourier transforms, Frequency-domain analysis, FIR filter BibRef

Li, S., Zhang, W., Cui, Y., Cheng, H.V., Yu, W.,
Joint Design of Measurement Matrix and Sparse Support Recovery Method via Deep Auto-Encoder,
SPLetters(26), No. 12, December 2019, pp. 1778-1782.
IEEE DOI 2001
compressed sensing, computational complexity, learning (artificial intelligence), signal reconstruction, grant-free massive access BibRef

Zhu, H., Liu, F., Li, J.,
Computationally Efficient Sinusoidal Parameter Estimation From Signed Measurements: ADMM Approaches,
SPLetters(26), No. 12, December 2019, pp. 1798-1802.
IEEE DOI 2001
compressed sensing, computational complexity, convex programming, parameter estimation, signal reconstruction, update steps design, log-norm BibRef

Li, Y., He, Q., Blum, R.S.,
On the Product of Two Correlated Complex Gaussian Random Variables,
SPLetters(27), 2020, pp. 16-20.
IEEE DOI 2001
Product of correlated complex Gaussian random variables, joint probability density function, non-zero means and arbitrary variances BibRef

El-Laham, Y., Bugallo, M.F.,
Stochastic Gradient Population Monte Carlo,
SPLetters(27), 2020, pp. 46-50.
IEEE DOI 2001
BibRef

Chavali, V., Wage, K.E.,
Cross Term Decay in Multiplicative Processors,
SPLetters(27), 2020, pp. 56-60.
IEEE DOI 2001
Program processors, Gratings, Probability density function, Random variables, Sensor arrays, Geometry, distribution of sum of products of independent complex Gaussian random variables BibRef

Gavaskar, R.G., Chaudhury, K.N.,
On the Proof of Fixed-Point Convergence for Plug-and-Play ADMM,
SPLetters(26), No. 12, December 2019, pp. 1817-1821.
IEEE DOI 2001
convergence of numerical methods, image denoising, image restoration, iterative methods, theorem proving, conver-gence analysis BibRef

Wang, G., Adhikary, A.R., Zhou, Z., Yang, Y.,
Generalized Constructions of Complementary Sets of Sequences of Lengths Non-Power-of-Two,
SPLetters(27), 2020, pp. 136-140.
IEEE DOI 2001
Complementary sets (CSs), Golay complemen-tary pair (GCP) BibRef

Benyamin, M.[Minas], Calder, J.[Jeff], Sundaramoorthi, G.[Ganesh], Yezzi, A.J.[Anthony J.],
Accelerated Variational PDEs for Efficient Solution of Regularized Inversion Problems,
JMIV(62), No. 1, January 2020, pp. 10-36.
Springer DOI 2001
BibRef

Sundaramoorthi, G.[Ganesh], Yezzi, A.J.[Anthony J.], Benyamin, M.[Minas],
Accelerated Optimization in the PDE Framework: Formulations for the Manifold of Diffeomorphisms,
SIIMS(15), No. 1, 2022, pp. 324-366.
DOI Link 2204
BibRef

Ma, K.[Kede], Duanmu, Z.F.[Zheng-Fang], Wang, Z.[Zhou], Wu, Q.B.[Qing-Bo], Liu, W.T.[Wen-Tao], Yong, H.W.[Hong-Wei], Li, H.L.[Hong-Liang], Zhang, L.[Lei],
Group Maximum Differentiation Competition: Model Comparison with Few Samples,
PAMI(42), No. 4, April 2020, pp. 851-864.
IEEE DOI 2003
Computational modeling, Predictive models, Analytical models, Streaming media, Complexity theory, Image quality, Resistance, streaming video quality-of-experience BibRef

Hong, T., Yavneh, I., Zibulevsky, M.,
Solving RED With Weighted Proximal Methods,
SPLetters(27), 2020, pp. 501-505.
IEEE DOI 2005
RED: REgularization by Denoising. Signal processing algorithms, Noise reduction, Inverse problems, Acceleration, Approximation algorithms, Minimization, weighting BibRef

Zhang, Z.[Zhen], Wang, S.[Shengzheng], Bian, W.[Wei],
Sign consistency for the linear programming discriminant rule,
PR(100), 2020, pp. 107083.
Elsevier DOI 2005
High-dimensional linear discriminant analysis, Sign consistency, Irrepresentability condition, Linear programming BibRef

Li, J.Y.[Jia-Yuan], Hu, Q.W.[Qing-Wu], Ai, M.Y.[Ming-Yao],
Robust Geometric Model Estimation Based on Scaled Welsch q-Norm,
GeoRS(58), No. 8, August 2020, pp. 5908-5921.
IEEE DOI 2007
Robustness, Estimation, Remote sensing, Optimization, Standards, Convex functions, Sensitivity, Image orientation, model fitting, robust feature matching (RFM) BibRef

Adamiak, K.[Krzysztof], Kim, H.[Hyongsuk], Slot, K.[Krzysztof],
Accelerating projections to kernel-induced spaces by feature approximation,
PRL(136), 2020, pp. 31-39.
Elsevier DOI 2008
Feature extraction, Kernel methods, Computational complexity BibRef

Zhang, S.[Sheng], Han, H.Y.[Hong-Yu], Jin, X.L.[Xing-Lian], Xia, Y.L.[Yi-Li],
Complementary Mean-Square Analysis of CNLMS Algorithm Using Pseudo-Energy-Conservation Method,
SPLetters(27), 2020, pp. 1345-1349.
IEEE DOI 2008
Steady-state, Signal processing algorithms, Mean square error methods, Transient analysis, steady-state analysis BibRef

Wang, K.[Kuan], Liu, Z.J.[Zhi-Jian], Lin, Y.J.[Yu-Jun], Lin, J.[Ji], Han, S.[Song],
Hardware-Centric AutoML for Mixed-Precision Quantization,
IJCV(128), No. 8-9, September 2020, pp. 2035-2048.
Springer DOI 2008
BibRef

Hacini, M.[Meriem], Hachouf, F.[Fella], Charef, A.[Abdelfatah],
A bi-directional fractional-order derivative mask for image processing applications,
IET-IPR(14), No. 11, September 2020, pp. 2512-2524.
DOI Link 2009
for two-dimensional fractional differentiation. BibRef

Li, B., Wu, N.,
Convergence Analysis of Gaussian SPAWN Under High-Order Graphical Models,
SPLetters(27), 2020, pp. 1725-1729.
IEEE DOI 2010
Convergence, Graphical models, Computational complexity, Mathematical model, Peer-to-peer computing, Belief propagation, Gaussian SPAWN BibRef

Bartolucci, F.[Francesco], Pandolfi, S.[Silvia],
An exact algorithm for time-dependent variational inference for the dynamic stochastic block model,
PRL(138), 2020, pp. 362-369.
Elsevier DOI 2010
Adjusted rand index, Expectation-maximization algorithm, Longitudinal data BibRef

Lauriola, I.[Ivano], Polato, M.[Mirko], Aiolli, F.[Fabio],
Learning deep kernels in the space of monotone conjunctive polynomials,
PRL(140), 2020, pp. 200-206.
Elsevier DOI 2012
Multiple kernel learning, Boolean kernels, Dot-product kernels, Representation learning BibRef

Hofmeyr, D.P.[David P.],
Fast Exact Evaluation of Univariate Kernel Sums,
PAMI(43), No. 2, February 2021, pp. 447-458.
IEEE DOI 2101
Kernel, Estimation, Probability distribution, Independent component analysis, Deconvolution, image reconstruction BibRef

Katakol, S.[Sudeep], Elbarashy, B.[Basem], Herranz, L.[Luis], van de Weijer, J.[Joost], López, A.M.[Antonio M.],
Distributed Learning and Inference With Compressed Images,
IP(30), 2021, pp. 3069-3083.
IEEE DOI 2103
Training, Degradation, Image coding, Semantics, Data models, Image restoration, Task analysis, Image compression, autonomous driving BibRef

Ali, A.[Anum], Moinuddin, M.[Muhammad], Al-Naffouri, T.Y.[Tareq Y.],
The NLMS Is Steady-State Schur-Convex,
SPLetters(28), 2021, pp. 389-393.
IEEE DOI 2103
Normalized Least Mean Squares. Steady-state, Correlation, Eigenvalues and eigenfunctions, Signal processing algorithms, Signal to noise ratio, Standards, Schur-convexity BibRef

Qiao, H.[Heng],
On the Performance of the SPICE Method,
SPLetters(28), 2021, pp. 543-547.
IEEE DOI 2103
spectrum estimation. SPICE, Robustness, Tuning, Spectral analysis, Signal processing algorithms, Monte Carlo methods, quotient property BibRef

Panagakis, Y.[Yannis], Kossaifi, J.[Jean], Chrysos, G.G.[Grigorios G.], Oldfield, J.[James], Nicolaou, M.A.[Mihalis A.], Anandkumar, A.[Anima], Zafeiriou, S.P.[Stefanos P.],
Tensor Methods in Computer Vision and Deep Learning,
PIEEE(109), No. 5, May 2021, pp. 863-890.
IEEE DOI 2105
Deep learning, Visualization, Tensors, Data analysis, Semantics, Memory management, tensor methods BibRef

Kalaivani, A., Swetha, K.,
An Enhanced Bidirectional Insertion Sort Over Classical Insertion Sort,
IJIG(21), No. 2 2021, pp. 2150024.
DOI Link 2105
BibRef

Lourakis, M.[Manolis], Terzakis, G.[George],
A Globally Optimal Method for the PnP Problem with MRP Rotation Parameterization,
ICPR21(3058-3063)
IEEE DOI 2105
Robustness, Computational efficiency, Mathematical model, Least mean squares methods BibRef

Gu, B.[Bin], Xiong, Z.[Ziran], Yu, S.Y.[Shu-Yang], Zheng, G.S.[Guan-Sheng],
A kernel path algorithm for general parametric quadratic programming problem,
PR(116), 2021, pp. 107941.
Elsevier DOI 2106
Kernel path, QR decomposition, Parametric quadratic programming, Cross validation BibRef

Wadayama, T.[Tadashi], Takabe, S.[Satoshi],
Chebyshev Periodical Successive Over-Relaxation for Accelerating Fixed-Point Iterations,
SPLetters(28), 2021, pp. 907-911.
IEEE DOI 2106
Chebyshev approximation, Convergence, Jacobian matrices, Acceleration, Eigenvalues and eigenfunctions, Gradient methods, proximal methods BibRef

Angle, R.B.[R. Blair], Streit, R.L.[Roy L.], Efe, M.[Murat],
A Low Computational Complexity JPDA Filter With Superposition,
SPLetters(28), 2021, pp. 1031-1035.
IEEE DOI 2106
Bayes methods, Computational complexity, Clutter, Target tracking, Probability distribution, Probability density function, intensity functions BibRef

Marrelec, G.[Guillaume], Giron, A.[Alain],
Automated Extraction of Mutual Independence Patterns Using Bayesian Comparison of Partition Models,
PAMI(43), No. 7, July 2021, pp. 2299-2313.
IEEE DOI 2106
Bayes methods, Gaussian distribution, Numerical models, Markov processes, Monte Carlo methods, Covariance matrices, parallel tempering BibRef

Berglund, E.[Erik], Magnússon, S.[Sindri], Johansson, M.[Mikael],
Distributed Newton Method Over Graphs: Can Sharing of Second-Order Information Eliminate the Condition Number Dependence?,
SPLetters(28), 2021, pp. 1180-1184.
IEEE DOI 2106
Signal processing algorithms, Complexity theory, Optimization, Peer-to-peer computing, Convergence, Gradient methods, optimization BibRef

Dong, G.Z.[Guo-Zhi], Hintermueller, M.[Michael], Zhang, Y.[Ye],
A Class of Second-Order Geometric Quasilinear Hyperbolic PDEs and Their Application in Imaging,
SIIMS(14), No. 2, 2021, pp. 645-688.
DOI Link 2107
BibRef

Bungert, L.[Leon], Hait-Fraenkel, E.[Ester], Papadakis, N.[Nicolas], Gilboa, G.[Guy],
Nonlinear Power Method for Computing Eigenvectors of Proximal Operators and Neural Networks,
SIIMS(14), No. 3, 2021, pp. 1114-1148.
DOI Link 2108
BibRef

Colonnese, S.[Stefania], Conti, F.[Francesco], Biagi, M.[Mauro], Scarano, G.[Gaetano],
Cross-Burg Algorithm for Single-Input Two-Outputs Autoregressive Modeling,
SPLetters(28), 2021, pp. 1640-1644.
IEEE DOI 2109
Signal processing algorithms, Lattices, Mathematical model, Numerical models, Estimation, Data models, Signal to noise ratio, Cross-Burg Method BibRef

Oymak, S.[Samet],
Provable Super-Convergence With a Large Cyclical Learning Rate,
SPLetters(28), 2021, pp. 1645-1649.
IEEE DOI 2109
Eigenvalues and eigenfunctions, Convergence, Jacobian matrices, Standards, Deep learning, Signal processing algorithms, Schedules, Gradient methods BibRef

Sun, Y.[Ya], Mai, S.J.[Si-Jie], Hu, H.F.[Hai-Feng],
Learning to Balance the Learning Rates Between Various Modalities via Adaptive Tracking Factor,
SPLetters(28), 2021, pp. 1650-1654.
IEEE DOI 2109
Optimization, Signal processing algorithms, Convergence, Training, Task analysis, Adaptive equalizers, Prediction algorithms, bilevel directional optimization BibRef

Zhao, X.L.[Xiang-Ling], Yuan, Y.[Yuan], Dong, Y.[Yun], Zhao, R.[Ren],
Optimization approach to the aircraft weight and balance problem with the centre of gravity envelope constraints,
IET-ITS(15), No. 10, 2021, pp. 1269-1286.
DOI Link 2109
BibRef

Cancela, B.[Brais], Alonso-Betanzos, A.[Amparo],
Wavefront Marching Methods: A Unified Algorithm to Solve Eikonal and Static Hamilton-Jacobi Equations,
PAMI(43), No. 11, November 2021, pp. 4177-4188.
IEEE DOI 2110
Mathematical model, Complexity theory, Computational efficiency, anisotropic BibRef

Hadifar, A.[Amir], Deleu, J.[Johannes], Develder, C.[Chris], Demeester, T.[Thomas],
Exploration of block-wise dynamic sparseness,
PRL(151), 2021, pp. 187-192.
Elsevier DOI 2110
Neural network, Dynamic sparseness, Block-wise matrix multiplication BibRef

Karimi, P.[Parisa], Zhao, Z.Z.[Zhi-Zhen], Butala, M.D.[Mark D.], Kamalabadi, F.[Farzad],
Quantification of Mismatch Error in Randomly Switching Linear State-Space Models,
SPLetters(28), 2021, pp. 2008-2012.
IEEE DOI 2110
Superluminescent diodes, Kalman filters, Switches, Trajectory, Mathematical models, Dynamical systems, State-space methods, model mismatch BibRef

Yang, R.H.[Rong-Hua], Deng, C.[Chang], Yu, K.[Kegen], Li, Z.[Zhao], Pan, L.X.[Lei-Xilan],
A New Way for Cartesian Coordinate Transformation and Its Precision Evaluation,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Paleologu, C.[Constantin], Benesty, J.[Jacob], Ciochina, S.[Silviu],
Data-Reuse Recursive Least-Squares Algorithms,
SPLetters(29), 2022, pp. 752-756.
IEEE DOI 2204
Signal processing algorithms, Convergence, Covariance matrices, Computational complexity, Indexes, Kalman filters, tracking BibRef

Ji, F.F.[Fan-Fan], Shuai, H.[Hui], Yuan, X.T.[Xiao-Tong],
A globally convergent approximate Newton method for non-convex sparse learning,
PR(126), 2022, pp. 108560.
Elsevier DOI 2204
Sparse learning, Newton-type method, Linear models, Quadratic approximation, Iterative hard thresholding BibRef

Xu, Y.Y.[Yang-Yang], Xu, Y.[Yibo], Yan, Y.G.[Yong-Gui], Chen, J.[Jie],
Distributed Stochastic Inertial-Accelerated Methods with Delayed Derivatives for Nonconvex Problems,
SIIMS(15), No. 2, 2022, pp. 550-590.
DOI Link 2205
BibRef

Huang, C.J.[Chu-Jun], Shao, M.J.[Ming-Jie], Ma, W.K.[Wing-Kin], So, A.M.C.[Anthony Man-Cho],
SISAL Revisited,
SIIMS(15), No. 2, 2022, pp. 591-624.
DOI Link 2205
Simplex identification via split augmented Lagrangian. BibRef

Guo, K.[Kai], Zheng, D.D.[Dong-Dong], Li, J.[Jianyong],
Optimal Bounded Ellipsoid Identification With Deterministic and Bounded Learning Gains: Design and Application to Euler-Lagrange Systems,
Cyber(52), No. 10, October 2022, pp. 10800-10813.
IEEE DOI 2209
Artificial neural networks, Heuristic algorithms, Uncertainty, Ellipsoids, Upper bound, Convergence, Adaptive control, optimal bounded ellipsoid (OBE) BibRef

Routtenberg, T.[Tirza], Tabrikian, J.[Joseph],
Bayesian Periodic Cramér-Rao Bound,
SPLetters(29), 2022, pp. 1878-1882.
IEEE DOI 2209
Bayes methods, Parameter estimation, Optimization, Minimization, Estimation, Phase estimation, System analysis and design, periodic parameter estimation BibRef

Han, A.[Andi], Gao, J.B.[Jun-Bin],
Improved Variance Reduction Methods for Riemannian Non-Convex Optimization,
PAMI(44), No. 11, November 2022, pp. 7610-7623.
IEEE DOI 2210
Complexity theory, Optimization, Manifolds, Convergence, Convex functions, Training, Principal component analysis, batch size adaptation BibRef

Liu, F.H.[Fang-Hui], Huang, X.L.[Xiao-Lin], Chen, Y.D.[Yu-Dong], Suykens, J.A.K.[Johan A. K.],
Towards a Unified Quadrature Framework for Large-Scale Kernel Machines,
PAMI(44), No. 11, November 2022, pp. 7975-7988.
IEEE DOI 2210
Kernel, Monte Carlo methods, Convergence, Costs, Weight measurement, Transforms, Standards, Random features, quadrature methods, kernel approximation BibRef

Maalouf, A.[Alaa], Jubran, I.[Ibrahim], Feldman, D.[Dan],
Fast and Accurate Least-Mean-Squares Solvers for High Dimensional Data,
PAMI(44), No. 12, December 2022, pp. 9977-9994.
IEEE DOI 2212
Approximation algorithms, Matrix decomposition, Big Data, Linear regression, Codes, Voltage control, Tuning, Regression, Big Data BibRef

Tian, X.[Xiang], Chen, H.[Hui], He, M.M.[Meng-Meng], Wang, W.Q.[Wen-Qin],
Fast Beampattern Synthesis Algorithm for Flexible Conformal Array,
SPLetters(29), 2022, pp. 2417-2421.
IEEE DOI 2212
Change wing shapes. Optimization, Convex functions, Signal processing algorithms, Transforms, Strain, Simulation, Shape, Flexible conformal array, alternating direction method of multipliers (ADMM) BibRef

Wang, J.[Jinfu], Yang, F.[Feiran], Yang, J.[Jun],
Insights Into the MMSE-Based Frequency-Invariant Beamformers for Uniform Circular Arrays,
SPLetters(29), 2022, pp. 2432-2436.
IEEE DOI 2212
Jacobian matrices, Weight measurement, Array signal processing, Mean square error methods, Apertures, White noise, minimum mean square error BibRef

Zhang, H.R.[Heng-Ru], Qiu, Y.[Ying], Zhu, K.L.[Ke-Lin], Min, F.[Fan],
Lower bound estimation of recommendation error through user uncertainty modeling,
PR(136), 2023, pp. 109171.
Elsevier DOI 2301
Magic barrier estimation, Mixture of exponential power, Recommender system, Uncertainty modeling BibRef

Chouzenoux, E.[Emilie], Contreras, A.[Andres], Pesquet, J.C.[Jean-Christophe], Savanier, M.[Marion],
Convergence Results for Primal-Dual Algorithms in the Presence of Adjoint Mismatch,
SIIMS(16), No. 1, 2023, pp. 1-34.
DOI Link 2301
BibRef

Strossner, C.[Christoph], Kressner, D.[Daniel],
Low-Rank Tensor Approximations for Solving Multimarginal Optimal Transport Problems,
SIIMS(16), No. 1, 2023, pp. 169-191.
DOI Link 2302
BibRef

Mengüç, E.C.[Engin Cemal], Acir, N.[Nurettin], Mandic, D.P.[Danilo P.],
A Class of Online Censoring Based Quaternion-Valued Least Mean Square Algorithms,
SPLetters(30), 2023, pp. 244-248.
IEEE DOI 2303
Signal processing algorithms, Quaternions, Calculus, Cost function, Convergence, Filtering, Technological innovation, big data streams BibRef

Bretin, E.[Elie], Millien, P.[Pierre], Seppecher, L.[Laurent],
Stability for Finite Element Discretization of Some Inverse Parameter Problems from Internal Data: Application to Elastography,
SIIMS(16), No. 1, 2023, pp. 340-367.
DOI Link 2303
BibRef

Song, Y.[Yue], Sebe, N.[Nicu], Wang, W.[Wei],
Fast Differentiable Matrix Square Root and Inverse Square Root,
PAMI(45), No. 6, June 2023, pp. 7367-7380.
IEEE DOI 2305
Covariance matrices, Matrix decomposition, Decorrelation, Transforms, Deep learning, Task analysis, neural style transfer BibRef

Liang, J.[Jing], Li, K.[Ke], Yu, K.J.[Kun-Jie], Yue, C.T.[Cai-Tong], Li, Y.X.[Ya-Xin], Song, H.[Hui],
A Novel Differential Evolution Algorithm Based on Local Fitness Landscape Information for Optimization Problems,
IEICE(E106-D), No. 5, May 2023, pp. 601-616.
WWW Link. 2305
BibRef

Gao, G.Y.[Guang-Yu], Han, B.[Bo], Fu, Z.[Zhenwu], Tong, S.S.[Shan-Shan],
A Fast Data-Driven Iteratively Regularized Method with Convex Penalty for Solving Ill-Posed Problems,
SIIMS(16), No. 2, 2023, pp. 640-670.
DOI Link 2306
BibRef

Fontana, F.[Federico], Bozzo, E.[Enrico], Bernardini, A.[Alberto],
Extended Fixed-Point Methods for the Computation of Virtual Analog Models,
SPLetters(30), 2023, pp. 848-852.
IEEE DOI 2307
Jacobian matrices, Convergence, Mathematical models, Digital filters, Computational modeling, virtual analog (VA) BibRef

Zhai, Z.[Zheng], Chen, H.C.[Heng-Chao], Sun, Q.[Qiang],
Bounded Projection Matrix Approximation With Applications to Community Detection,
SPLetters(30), 2023, pp. 957-961.
IEEE DOI 2308
Sparse matrices, Signal processing algorithms, Convergence, Approximation algorithms, Limiting, Convex functions, projection matrix approximation BibRef

Xie, Y.[Yujia], Su, X.H.[Xin-Hua], Ge, H.[Huanmin],
RIP Analysis for L1/Lp (p>1) Minimization Method,
SPLetters(30), 2023, pp. 997-1001.
IEEE DOI 2309
BibRef

Greige, M.[Marc], Karfoul, A.[Ahmad], Merlet, I.[Isabelle], Jeannès, R.L.B.[Régine Le Bouquin],
An Optimized Dictionary-Based Model Identification Method in the Scope of Brain Effective Connectivity,
SPLetters(30), 2023, pp. 1002-1006.
IEEE DOI 2309
BibRef

Wang, J.[Jie], Lu, L.[Lu], Shi, L.[Long], Zhu, G.[Guangya], Yang, X.M.[Xiao-Min],
Euclidean Direction Search Algorithm Based on Maximum Correntropy Criterion,
SPLetters(30), 2023, pp. 1032-1036.
IEEE DOI 2309
BibRef

Han, H.Y.[Hong-Yu], Zhang, S.[Sheng], Huang, F.[Fuyi],
Interval-Extraction Affine Projection Algorithm,
SPLetters(30), 2023, pp. 1632-1636.
IEEE DOI 2311
BibRef

Arjas, A.[Arttu], Sillanpaa, M.J.[Mikko J.], Hauptmann, A.S.[Andreas S.],
Sequential Model Correction for Nonlinear Inverse Problems,
SIIMS(16), No. 4, 2023, pp. 2015-2039.
DOI Link 2312
BibRef

Li, P.J.[Pei-Jun], Liang, Y.[Ying], Wang, Y.L.[Yu-Liang],
A Data-Assisted Two-Stage Method for the Inverse Random Source Problem,
SIIMS(16), No. 4, 2023, pp. 1929-1952.
DOI Link 2312
BibRef

Kullberg, A.[Anton], Skoglund, M.A.[Martin A.], Skog, I.[Isaac], Hendeby, G.[Gustaf],
On the Relationship Between Iterated Statistical Linearization and Quasi-Newton Methods,
SPLetters(30), 2023, pp. 1777-1781.
IEEE DOI 2312
BibRef

Chu, H.Y.[Hao-Yu], Wei, S.[Shikui], Lu, Q.M.[Qi-Ming], Zhao, Y.[Yao],
Improving neural ordinary differential equations via knowledge distillation,
IET-CV(18), No. 2, 2024, pp. 304-314.
DOI Link 2403
image classification, neural nets BibRef

Delmas, J.P.[Jean-Pierre], Abeida, H.[Habti],
Generalization of Whittle's Formula to Compound-Gaussian Processes,
SPLetters(31), 2024, pp. 746-750.
IEEE DOI 2403
Gaussian processes, Gaussian distribution, Covariance matrices, Generators, Random processes, Estimation, Correlation, Student's t processes BibRef

Liu, Y.L.[Yu-Lan], Zhou, Y.Y.[Yu-Yang], Lin, R.R.[Rong-Rong],
The Proximal Operator of the Piece-Wise Exponential Function,
SPLetters(31), 2024, pp. 894-898.
IEEE DOI 2404
Optimization, Compressed sensing, Signal processing algorithms, Vectors, Mathematical models, Shape, Neural networks, proximal operator BibRef

Besson, O.[Olivier],
Stein's Approach Based MVDR Filter Modification,
SPLetters(31), 2024, pp. 924-928.
IEEE DOI 2404
Minimum Variance Distortionless Response. Vectors, Maximum likelihood estimation, Covariance matrices, Signal to noise ratio, Training, Minimization, Loading, Stein unbiased risk estimation BibRef

Narnhofer, D.[Dominik], Habring, A.[Andreas], Holler, M.[Martin], Pock, T.[Thomas],
Posterior-Variance-Based Error Quantification for Inverse Problems in Imaging,
SIIMS(17), No. 1, 2024, pp. 301-333.
DOI Link 2404
BibRef

Ambartsoumian, G.[Gaik], Jebelli, M.J.L.[Mohammad J. Latifi], Mishra, R.K.[Rohit K.],
Numerical Implementation of Generalized V-Line Transforms on 2D Vector Fields and their Inversions,
SIIMS(17), No. 1, 2024, pp. 595-631.
DOI Link 2404
BibRef

Devlin, L.[Lee], Carter, M.[Matthew], Horridge, P.[Paul], Green, P.L.[Peter L.], Maskell, S.[Simon],
The No-U-Turn Sampler as a Proposal Distribution in a Sequential Monte Carlo Sampler Without Accept/Reject,
SPLetters(31), 2024, pp. 1089-1093.
IEEE DOI 2405
Proposals, Monte Carlo methods, Kernel, Transforms, Vectors, Bayes methods, Space exploration, Bayesian inference, sequential Monte Carlo BibRef

Gu, Z.[Zhi], Zhou, Z.C.[Zheng-Chun], Adhikary, A.R.[Avik Ranjan], Fan, P.Z.[Ping-Zhi], Yang, Y.[Yang],
Generalized Zadoff-Chu Sequences With Low PMEPR Property,
SPLetters(31), 2024, pp. 1174-1178.
IEEE DOI 2405
OFDM, Codes, Signal processing algorithms, Symbols, Complexity theory, Systematics, Optimization, Zadoff-Chu sequence BibRef

Yu, H.P.[Hai-Peng], Chang, G.B.[Guo-Bin], Zhang, S.[Shubi],
Improved Algorithm for Efficient Computation of Slepian Functions Over Arbitrary Regions on the Sphere,
SPLetters(31), 2024, pp. 1189-1193.
IEEE DOI 2405
Signal processing algorithms, Computational efficiency, Software algorithms, Computational complexity, improvement BibRef

Zhong, S.M.[Shui-Ming], Lyu, H.[Huan], Lu, X.X.[Xiao-Xiang], Wang, B.W.[Bao-Wei], Wang, D.C.[Ding-Cheng],
A New Sufficient and Necessary Condition for Testing Linear Separability Between Two Sets,
PAMI(46), No. 6, June 2024, pp. 4160-4173.
IEEE DOI 2405
Computational modeling, Support vector machines, Time complexity, Testing, Training, Task analysis, Symbols, Classification, sphere model BibRef

Wang, C.G.[Chen-Guang], Yu, Z.[Zhouliang], McAleer, S.[Stephen], Yu, T.S.[Tian-Shu], Yang, Y.[Yaodong],
ASP: Learn a Universal Neural Solver!,
PAMI(46), No. 6, June 2024, pp. 4102-4114.
IEEE DOI 2405
Training, Traveling salesman problems, Optimization, Vehicle routing, Scalability, Adaptation models, Standards, policy space response oracles BibRef

Zhang, X.Y.[Xin-Yue], Peng, L.Z.[Liang-Zu], Xu, W.T.[Wan-Ting], Kneip, L.[Laurent],
Accelerating Globally Optimal Consensus Maximization in Geometric Vision,
PAMI(46), No. 6, June 2024, pp. 4280-4297.
IEEE DOI 2405
Cameras, Fitting, Computational modeling, Pose estimation, Optimization, Branch and bound, consensus maximization, interval stabbing BibRef

Jin, X.Y.[Xiao-Yue], Li, H.J.[Hao-Jing], Yu, D.X.[Deng-Xiu], Wang, Z.[Zhen], Li, X.L.[Xue-Long],
Topological optimization of continuous action iterated dilemma based on finite-time strategy using DQN,
PRL(182), 2024, pp. 133-139.
Elsevier DOI 2405
Evolutionary game theory, Topological optimization, Convergence analysis, Lyapunov function BibRef

Lopez, C.A.[Carlos Alejandro], Riba, J.[Jaume],
On the Convergence of Block Majorization-Minimization Algorithms on the Grassmann Manifold,
SPLetters(31), 2024, pp. 1314-1318.
IEEE DOI 2405
Manifolds, Convergence, Signal processing algorithms, Cost function, Signal processing, Principal component analysis, convergence BibRef

Diao, Q.K.[Qian-Kun], Xu, D.P.[Dong-Po], Sun, S.N.[Shu-Ning], Mandic, D.P.[Danilo P.],
Price's Theorem for Quaternion Variables,
SPLetters(31), 2024, pp. 1424-1428.
IEEE DOI 2405
Quaternions, Vectors, Calculus, Covariance matrices, Random variables, Filtering algorithms, Sun, GHR calculus, quaternion statistics BibRef

Mulchandani, M.[Mona], Nair, P.S.[Pramod S.],
EBMICQL: Improving Efficiency of Blockchain Miner Pools via Incremental and Continuous Q-Learning Framework,
IJIG(24), No. 3, May 2024, pp. 2450034.
DOI Link 2406
BibRef

Deen, O.[Owen], Waller, C.R.[Colton River], Ward, J.P.[John Paul],
Fast and Accurate Log-Determinant Approximations,
SPLetters(31), 2024, pp. 1520-1524.
IEEE DOI 2406
Sparse matrices, Splines (mathematics), Approximation algorithms, Indexes, Signal processing algorithms, Laplace equations, Vectors, sparse matrices BibRef

Gillis, N.[Nicolas], Luce, R.[Robert],
Checking the Sufficiently Scattered Condition Using a Global Non-Convex Optimization Software,
SPLetters(31), 2024, pp. 1610-1614.
IEEE DOI 2406
Optimization, Matrix decomposition, Vectors, Software, Principal component analysis, Machine learning, non-convex quadra- tic optimization BibRef

Ziou, D.[Djemel],
Using Maximum Weighted Likelihood to Derive Lehmer and Hölder Families of Means,
SPLetters(31), 2024, pp. 1625-1629.
IEEE DOI 2406
Probability density function, Maximum likelihood estimation, Arithmetic, Neural networks, Harmonic analysis, Shape, weighted data BibRef

Walden, A.T.,
Generating Different Gaussian Multivariate Processes With Identical Graphs,
SPLetters(31), 2024, pp. 1640-1644.
IEEE DOI 2406
Signal processing algorithms, Reactive power, Time series analysis, Eigenvalues and eigenfunctions, Vectors, reachability matrix BibRef

Tan, H.Y.[Hong Ye], Mukherjee, S.[Subhadip], Tang, J.Q.[Jun-Qi], Schonlieb, C.B.[Carola-Bibiane],
Provably Convergent Plug-and-Play Quasi-Newton Methods,
SIIMS(17), No. 2, 2024, pp. 785-819.
DOI Link 2407
BibRef

Miao, Z.W.[Zheng-Wei], Luo, H.[Hui], Li, M.H.[Mei-Hui], Zhang, J.L.[Jian-Lin],
COLAFormer: Communicating local-global features with linear computational complexity,
PR(157), 2025, pp. 110870.
Elsevier DOI 2409
Vision transformer, Image classification, Computational complexity, Feature clustering BibRef

Diao, Q.K.[Qian-Kun], Liu, J.L.[Jin-Lan], Zhang, N.M.[Nai-Min], Xu, D.P.[Dong-Po],
An Iterative Algorithm for Quaternion Eigenvalue Problems in Signal Processing,
SPLetters(31), 2024, pp. 2505-2509.
IEEE DOI 2410
Quaternions, Eigenvalues and eigenfunctions, Signal processing algorithms, Calculus, Optimization, Convergence, quaternion projected gradient ascent BibRef

Shi, W.T.[Wan-Ting], Xia, Y.[Yili], Pei, W.J.[Wen-Jiang],
Widely Linear Momentum LMS Algorithm for Second Order Noncircular Signals and Performance Analysis,
SPLetters(31), 2024, pp. 2235-2239.
IEEE DOI 2410
widely linear momentum least mean squares. Convergence, Vectors, Covariance matrices, Signal processing algorithms, Steady-state, Upper bound, Standards, widely linear momentum LMS (WLMLMS) BibRef

Fu, Y.Z.[Yu-Zhe], Zhou, C.C.[Chang-Chun], Huang, T.[Tianling], Han, E.[Eryi], He, Y.F.[Yi-Fan], Jiao, H.L.[Hai-Long],
SoftAct: A High-Precision Softmax Architecture for Transformers Supporting Nonlinear Functions,
CirSysVideo(34), No. 9, September 2024, pp. 8912-8923.
IEEE DOI 2410
Hardware, Transformers, Computer architecture, Quantization (signal), Costs, Convolution, Inference algorithms, overall efficiency BibRef

Wang, R.[Rui], Zhang, C.[Chuwen], Pu, S.[Shanwen], Gao, J.J.[Jian-Jun], Wen, Z.[Zaiwen],
A Customized Augmented Lagrangian Method for Block-Structured Integer Programming,
PAMI(46), No. 12, December 2024, pp. 9439-9455.
IEEE DOI 2411
Integer programming, IP networks, Convex functions, Convergence, Programming, Machine learning algorithms, Lagrangian functions, convergence BibRef

Xiong, H.[Hao], Tang, Y.[Yehui], Ye, X.Y.[Xin-Yu], Yan, J.C.[Jun-Chi],
Circuit Design and Efficient Simulation of Quantum Inner Product and Empirical Studies of Its Effect on Near-Term Hybrid Quantum-Classic Machine Learning,
CVPR24(26162-26170)
IEEE DOI 2410
Computers, Pipelines, Qubit, Quantum mechanics, Machine learning, Self-supervised learning, Complexity theory, quantum circuits BibRef

Hong, S.[Seongmin], Park, I.[Inbum], Chun, S.Y.[Se Young],
On the Robustness of Normalizing Flows for Inverse Problems in Imaging,
ICCV23(10711-10721)
IEEE DOI 2401
BibRef

Huang, Z.Z.[Zhong-Zhan], Liang, M.[Mingfu], Qin, J.H.[Jing-Hui], Zhong, S.S.[Shan-Shan], Lin, L.[Liang],
Understanding Self-attention Mechanism via Dynamical System Perspective,
ICCV23(1412-1422)
IEEE DOI 2401
BibRef

Wu, W.H.[Wen-Hao], Song, Y.X.[Yu-Xin], Sun, Z.[Zhun], Wang, J.D.[Jing-Dong], Xu, C.[Chang], Ouyang, W.L.[Wan-Li],
What Can Simple Arithmetic Operations Do for Temporal Modeling?,
ICCV23(13666-13676)
IEEE DOI Code:
WWW Link. 2401
BibRef

Reddy, N.K.K.[Nareddy Kartheek Kumar], Killedar, V.[Vinayak], Seelamantula, C.S.[Chandra Sekhar],
Quantized Generative Models for Solving Inverse Problems,
REDLCV23(1520-1525)
IEEE DOI 2401
BibRef

Liu, X.C.[Xing-Chao], Wu, L.[Lemeng], Zhang, S.J.[Shu-Jian], Gong, C.Y.[Cheng-Yue], Ping, W.[Wei], Liu, Q.[Qiang],
FlowGrad: Controlling the Output of Generative ODEs with Gradients,
CVPR23(24335-24344)
IEEE DOI 2309
BibRef

Dagès, T.[Thomas], Cohen, L.D.[Laurent D.], Bruckstein, A.M.[Alfred M.],
A model is worth tens of thousands of examples for estimation and thousands for classification,
PR(157), 2025, pp. 110904.
Elsevier DOI 2409
BibRef
Earlier:
A Model is Worth Tens of Thousands of Examples,
SSVM23(223-235).
Springer DOI 2307
Deep learning, Model-based methods, Sample complexity BibRef

Xue, H.[Hao], Zeng, X.[Xia], Lin, W.[Wang], Yang, Z.F.[Zheng-Feng], Peng, C.[Chao], Zeng, Z.B.[Zhen-Bing],
An RNN-Based Framework for the MILP Problem in Robustness Verification of Neural Networks,
ACCV22(I:571-586).
Springer DOI 2307
Mixed-Integer Linear Programming. BibRef

Guastini, M.[Mara], Rajkovic, M.[Marko], Rumpf, M.[Martin], Wirth, B.[Benedikt],
The Variational Approach to the Flow of Sobolev-Diffeomorphisms Model,
SSVM23(551-564).
Springer DOI 2307
BibRef

Shabani, S.[Shima], Breuß, M.[Michael],
An Efficient Line Search for Sparse Reconstruction,
SSVM23(471-483).
Springer DOI 2307
Find local minimum BibRef

Gofer, E.[Eyal], Gilboa, G.[Guy],
Theoretical Foundations for Pseudo-inversion of Nonlinear Operators,
SSVM23(29-41).
Springer DOI 2307
BibRef

Kahl, M.[Max], Petra, S.[Stefania], Schnörr, C.[Christoph], Steidl, G.[Gabriele], Zisler, M.[Matthias],
On the Remarkable Efficiency of Smart,
SSVM23(418-430).
Springer DOI 2307
BibRef

Buskulic, N.[Nathan], Quéau, Y.[Yvain], Fadili, J.[Jalal],
Convergence Guarantees of Overparametrized Wide Deep Inverse Prior,
SSVM23(406-417).
Springer DOI 2307
BibRef

Wang, S.[Shida], Fadili, J.[Jalal], Ochs, P.[Peter],
A Quasi-Newton Primal-dual Algorithm with Line Search,
SSVM23(444-456).
Springer DOI 2307
BibRef

Toft, C.[Carl], Bökman, G.[Georg], Kahl, F.[Fredrik],
Azimuthal Rotational Equivariance in Spherical Convolutional Neural Networks,
ICPR22(3808-3814)
IEEE DOI 2212
Training, Correlation, Convolution, Pipelines, Neural networks, Harmonic analysis BibRef

Yang, W.B.[Wen-Bin], Wang, Z.[Zijia], Ni, J.C.[Jia-Cheng], Chen, Q.[Qiang], Jia, Z.[Zhen],
A Low-Rank Tensor Bayesian Filter Framework For Multi-Modal Analysis,
ICIP22(3738-3742)
IEEE DOI 2211
Cloud computing, Tensors, Algebra, Image edge detection, Information filters, Bayes methods, Tensor, Bayesian filter, multi-modal edge cloud computing BibRef

Hammoumi, A.[Adam], Moreaud, M.[Maxime], Jolimaitre, E.[Elsa], Chevalier, T.[Thibaud], Klotz, M.[Michaela], Novikov, A.[Alexey],
Accelerating a Morphology-Preserving Adsorption Model by Deep Learning,
ICIP22(1851-1855)
IEEE DOI 2211
Alternate numerical simulations. Adaptation models, Adsorption, Computational modeling, Morphology, Predictive models, CNN, gas adsorption, mathematical morphology BibRef

An, D.S.[Dong-Sheng], Lei, N.[Na], Gu, X.F.[Xian-Feng],
Approximate Discrete Optimal Transport Plan with Auxiliary Measure Method,
ECCV22(XXIII:619-635).
Springer DOI 2211
BibRef

Görlitz, A.[Andreas], Möller, M.[Michael], Kolb, A.[Andreas],
FL0C: Fast L0 Cut Pursuit for Estimation of Piecewise Constant Functions,
ICIP22(3677-3681)
IEEE DOI 2211
Image segmentation, Estimation, Approximation algorithms, Minimization, Hardware, Partitioning algorithms, Piecewise Constant Mumford Shah BibRef

Wang, H.Y.[Huan-Yu], Zhang, W.[Wenhu], Su, S.H.[Shi-Hao], Wang, H.[Hui], Miao, Z.W.[Zhen-Wei], Zhan, X.[Xin], Li, X.[Xi],
SP-Net: Slowly Progressing Dynamic Inference Networks,
ECCV22(XI:223-240).
Springer DOI 2211
BibRef

Du, S.[Shian], Luo, Y.H.[Yi-Hong], Chen, W.[Wei], Xu, J.[Jian], Zeng, D.[Delu],
TO-FLOW: Efficient Continuous Normalizing Flows with Temporal Optimization adjoint with Moving Speed,
CVPR22(12560-12570)
IEEE DOI 2210
Training, Statistical analysis, Computational modeling, Ordinary differential equations, Self- semi- meta- Statistical methods BibRef

Exarchakis, G.[Georgios], Oubari, O.[Omar], Lenz, G.[Gregor],
A sampling-based approach for efficient clustering in large datasets,
CVPR22(12393-12402)
IEEE DOI 2210
Clustering methods, Clustering algorithms, Approximation algorithms, Complexity theory, Task analysis, Statistical methods BibRef

Wang, H.Y.[Huan-Yu], Li, S.Y.[Song-Yuan], Su, S.H.[Shi-Hao], Qin, Z.Q.[Ze-Qun], Li, X.[Xi],
RDI-Net: Relational Dynamic Inference Networks,
ICCV21(4601-4610)
IEEE DOI 2203
Adaptation models, Correlation, Adaptive systems, Convolution, Computational modeling, Aggregates, Optimization and learning methods BibRef

Rodríguez-Diez, V.[Vladímir], Martínez-Trinidad, J.F.[José F.], Carrasco-Ochoa, J.A., Lazo-Cortés, M.S.[Manuel S.], Olvera-López, J.A.[J. Arturo],
A Comparative Study of Two Algorithms for Computing the Shortest Reducts: MiLIT and MinReduct,
MCPR21(57-67).
Springer DOI 2108
BibRef

Laferrière, P.[Philippe], Laferrière, S.[Samuel], Dahdah, S.[Steven], Forbes, J.R.[James Richard], Paull, L.[Liam],
Deep Koopman Representation for Control over Images (DKRCI),
CRV21(158-164)
IEEE DOI 2108
Deep learning, Linear systems, Neural networks, Aerospace electronics, Nonlinear dynamical systems, Robots, dynamical systems BibRef

Anumasa, S.[Srinivas], Srijith, P.K.,
Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations,
WACV21(4052-4060)
IEEE DOI 2106
Uncertainty, Computational modeling, Neural networks, Computer architecture, Robustness BibRef

Vasilescu, M.A.O.[M. Alex O], Kim, E.[Eric], Zeng, X.S.[Xiao S.],
CausalX: Causal eXplanations and Block Multilinear Factor Analysis,
ICPR21(10736-10743)
IEEE DOI 2105
Tree data structures, Visualization, Tensors, Algebra, Computational modeling, Training data, Data models, causality, image analysis BibRef

Le, H.[Huu], Zach, C.[Christopher], Rosten, E.[Edward], Woodford, O.J.[Oliver J.],
Progressive Batching for Efficient Non-linear Least Squares,
ACCV20(III:506-522).
Springer DOI 2103
BibRef

Gui, Z., Wang, Y., Cui, Z., Peng, D., Wu, J., Ma, Z., Luo, S., Wu, H.,
Developing Apache Spark Based Ripley's K Functions for Accelerating Spatiotemporal Point Pattern Analysis,
ISPRS20(B4:545-552).
DOI Link 2012
BibRef

Yu, T.[Tan], Cai, Y.F.[Yun-Feng], Li, P.[Ping],
Toward Faster and Simpler Matrix Normalization via Rank-1 Update,
ECCV20(XIX:203-219).
Springer DOI 2011
BibRef

Chowdhury, S.[Samir], Needham, T.[Tom],
Gromov-Wasserstein Averaging in a Riemannian Framework,
Diff-CVML20(3676-3684)
IEEE DOI 2008
Extraterrestrial measurements, Couplings, Transmission line matrix methods, Manifolds, Task analysis, Covariance matrices BibRef

Henriques, J., Ehrhardt, S., Albanie, S., Vedaldi, A.,
Small Steps and Giant Leaps: Minimal Newton Solvers for Deep Learning,
ICCV19(4762-4771)
IEEE DOI 2004
approximation theory, conjugate gradient methods, convergence of numerical methods, differentiation, Convergence BibRef

Li, Q.X.[Qiu-Xian], Tian, Y.L.[You-Liang],
Rational Delegation Computing Using Information Theory and Game Theory Approach,
MMMod20(II:669-680).
Springer DOI 2003
BibRef

Wang, Z.C.[Zhi-Chao], Li, Q.[Qian], Li, G.[Gang], Xu, G.D.[Guan-Dong],
Polynomial Representation for Persistence Diagram,
CVPR19(6116-6125).
IEEE DOI 2002
BibRef

Barron, J.T.[Jonathan T.],
A General and Adaptive Robust Loss Function,
CVPR19(4326-4334).
IEEE DOI 2002
BibRef

Lichtenstein, M.[Moshe], Pai, G.[Gautam], Kimmel, R.[Ron],
Deep Eikonal Solvers,
SSVM19(38-50).
Springer DOI 1909
Deep learning for approximate solutions. BibRef

Deledalle, C.A.[Charles-Alban], Papadakis, N.[Nicolas], Salmon, J.[Joseph], Vaiter, S.[Samuel],
Refitting Solutions Promoted by L12 Sparse Analysis Regularizations with Block Penalties,
SSVM19(131-143).
Springer DOI 1909
BibRef

Hertrich, J.[Johannes], Bacák, M.[Miroslav], Neumayer, S.[Sebastian], Steidl, G.[Gabriele],
Minimal Lipschitz Extensions for Vector-Valued Functions on Finite Graphs,
SSVM19(183-195).
Springer DOI 1909
BibRef

Adilkhanov, A.N., Pavlov, A.V., Taimanov, I.A.,
Discrete Analog of the Jacobi Set for Vector Fields,
CTIC19(1-11).
Springer DOI 1901
BibRef

Wu, B.C.[Bi-Chen], Wan, A.[Alvin], Yue, X.Y.[Xiang-Yu], Jin, P.[Peter], Zhao, S.C.[Si-Cheng], Golmant, N.[Noah], Gholaminejad, A.[Amir], Gonzalez, J.[Joseph], Keutzer, K.[Kurt],
Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions,
CVPR18(9127-9135)
IEEE DOI 1812
Kernel, Computational modeling, Task analysis, Resource description framework, Aggregates, Standards BibRef

Tourani, S.[Siddharth], Shekhovtsov, A.[Alexander], Rother, C.[Carsten], Savchynskyy, B.[Bogdan],
MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models,
ECCV18(II: 264-281).
Springer DOI 1810
Max Product Linear Programming. BibRef

Orlowski, A.[Arkadiusz], Chmielewski, L.J.[Leszek J.],
Ulam Spiral and Prime-Rich Polynomials,
ICCVG18(522-533).
Springer DOI 1810
BibRef

López, M.A.[Marco A.], Marcial-Romero, J.R.[J. Raymundo], de Ita, G.[Guillermo], Moyao, Y.[Yolanda],
A Linear Time Algorithm for Computing #2SAT for Outerplanar 2-CNF Formulas,
MCPR18(72-81).
Springer DOI 1807
Satisfiability problem for two Conjunctive Normal Form formulas. BibRef

Wang, W.Q.[Wen-Qi], Aggarwal, V.[Vaneet], Aeron, S.[Shuchin],
Efficient Low Rank Tensor Ring Completion,
ICCV17(5698-5706)
IEEE DOI 1802
tensors, MPS representation: Matrix Product State. TR completion algorithm, alternating minimization algorithm, Tensile stress BibRef

Olsson, C., Carlsson, M., Andersson, F., Larsson, V.,
Non-convex Rank/Sparsity Regularization and Local Minima,
ICCV17(332-340)
IEEE DOI 1802
computational complexity, concave programming, convex programming, gradient methods, matrix algebra, minimisation, TV BibRef

Vogel, C.[Christoph], Pock, T.[Thomas],
A Primal Dual Network for Low-Level Vision Problems,
GCPR17(189-202).
Springer DOI 1711
BibRef

Heiss, T.[Teresa], Wagner, H.[Hubert],
Streaming Algorithm for Euler Characteristic Curves of Multidimensional Images,
CAIP17(I: 397-409).
Springer DOI 1708
Computation using data in sequence, not all at once. BibRef

Dong, S.M.[Shu-Min], Zhuang, X.D.[Xiao-Dong], Yu, J.[Jun], Wang, Y.[Ying], Zhao, B.[Bo],
The design and analysis of adjustment factor in Gerschgorin Criterion for Source Number Estimation,
ICIVC17(823-827)
IEEE DOI 1708
Algorithm design and analysis, Design methodology, Robustness, Signal to noise ratio, adjustment factor, colored noise, gerschgorin disk criterion, source number estimation. BibRef

Chen, C.[Cheng], Yang, C.,
Introducing an in-core hybrid LU implementation on heterogeneous systems,
ICIVC17(1084-1089)
IEEE DOI 1708
Microwave integrated circuits, Niobium, LU factorization, heterogeneous system, in-core BibRef

Wielgus, A., Zarzycki, J.,
Efficient Schur parametrization of near-stationary stochastic processes,
WSSIP17(1-5)
IEEE DOI 1707
Complexity theory, Covariance matrices, DH-HEMTs, Hilbert space, Image processing, Signal processing algorithms, Stochastic processes, Second-order nonstationary stochastic processes, complexity reduction, linear, Schur, parametrization BibRef

Liang, J.W.[Jing-Wei], Fadili, J.M.[Jalal M.], Peyre, G.[Gabriel],
On the convergence rates of proximal splitting algorithms,
ICIP14(4146-4150)
IEEE DOI 1502
Complexity theory BibRef

Arnold, D.G.[D. Gregory], Sturtz, K.[Kirk],
Complexity Analysis of ATR Algorithms Based on Invariants,
CVBVS00(27).
IEEE DOI 0006
BibRef

Zucker, S.W.,
Complexity and Confusion in Computational Vision,
SCIA99(Invited Talk). BibRef 9900

Zucker, S.W.[Steven W.],
Structural Scales in Computational Vision,
AIU96(130-141). BibRef 9600

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Ant Colony Optimization, Bee Colony Optimization .