14.5.5 Multiple Instance Learning

Chapter Contents (Back)
Learning. Multiple Instance Learning. Multiple-instance learning.

Chen, Y.X.[Yi-Xin], Bi, J.B.[Jin-Bo], Wang, J.Z.[James Z.],
MILES: Multiple-Instance Learning via Embedded Instance Selection,
PAMI(28), No. 12, December 2006, pp. 1931-1947.
IEEE DOI 0611
BibRef
Earlier: A2, A1, A3:
A Sparse Support Vector Machine Approach to Region-Based Image Categorization,
CVPR05(I: 1121-1128).
IEEE DOI 0507
Training labels on sets of instances not single instances. BibRef

McGovern, A.[Amy], Jensen, D.[David],
Optimistic pruning for multiple instance learning,
PRL(29), No. 9, 1 July 2008, pp. 1252-1260.
Elsevier DOI 0711
Multiple instance learning; Optimistic pruning; Chi-squared BibRef

Tao, Q.P.[Qing-Ping], Scott, S.D.[Stephen D.], Vinodchandran, N.V., Osugi, T.T.[Thomas Takeo], Mueller, B.[Brandon],
Kernels for Generalized Multiple-Instance Learning,
PAMI(30), No. 12, December 2008, pp. 2084-2098.
IEEE DOI 0811
BibRef

Fu, Z.Y.[Zhou-Yu], Robles-Kelly, A.[Antonio], Zhou, J.[Jun],
MILIS: Multiple Instance Learning with Instance Selection,
PAMI(33), No. 1, January 2011, pp. 958-977.
IEEE DOI 1104
Deals with collections of instances called bags. Each bag has instances for feature extraction. Large instance space. BibRef

Fu, Z.Y.[Zhou-Yu], Robles-Kelly, A.[Antonio],
An instance selection approach to Multiple instance Learning,
CVPR09(911-918).
IEEE DOI 0906
BibRef
Earlier:
Fast multiple instance learning via L1,2 logistic regression,
ICPR08(1-4).
IEEE DOI 0812
BibRef
And:
On Mixtures of Linear SVMs for Nonlinear Classification,
SSPR08(489-499).
Springer DOI 0812
BibRef

Bergeron, C.[Charles], Moore, G.[Gregory], Zaretzki, J.[Jed], Breneman, C.M.[Curt M.], Bennett, K.P.[Kristin P.],
Fast Bundle Algorithm for Multiple-Instance Learning,
PAMI(34), No. 6, June 2012, pp. 1068-1079.
IEEE DOI 1205
BibRef

Zhang, T.Z.[Tian-Zhu], Liu, S.[Si], Xu, C.S.[Chang-Sheng], Lu, H.Q.[Han-Qing],
M4L: Maximum margin Multi-instance Multi-cluster Learning for scene modeling,
PR(46), No. 10, October 2013, pp. 2711-2723.
Elsevier DOI 1306
Scene understanding; Maximum margin clustering; Multiple instance learning (MIL); Gaussian Mixture Model (GMM); Constrained Concave-Convex Procedure (CCCP) BibRef

Zhang, B.[Bang], Wang, Y.[Yang], Chen, F.[Fang],
Multilabel Image Classification Via High-Order Label Correlation Driven Active Learning,
IP(23), No. 3, March 2014, pp. 1430-1441.
IEEE DOI 1403
correlation methods BibRef

Zhang, B.[Bang], Wang, Y.[Yang], Wang, W.[Wei],
Batch mode active learning for multi-label image classification with informative label correlation mining,
WACV12(401-407).
IEEE DOI 1203
BibRef
And:
Multiple-Instance learning from multiple perspectives: Combining models for Multiple-Instance learning,
WACV12(481-487).
IEEE DOI 1203
BibRef

Herman, G.[Gunawan], Ye, G.T.[Ge-Tian], Wang, Y.[Yang], Xu, J.[Jie], Zhang, B.[Bang],
Multi-instance learning with relational information of instances,
WACV09(1-7).
IEEE DOI 0912
BibRef

Hong, R.C.[Ri-Chang], Wang, M.[Meng], Gao, Y.[Yue], Tao, D.C.[Da-Cheng], Li, X.L.[Xue-Long], Wu, X.D.[Xin-Dong],
Image Annotation by Multiple-Instance Learning With Discriminative Feature Mapping and Selection,
Cyber(44), No. 5, May 2014, pp. 669-680.
IEEE DOI 1405
correlation methods BibRef

Li, T., Wang, Y., Hong, R.C.[Ri-Chang], Wang, M.[Meng], Wu, X.D.[Xin-Dong],
pDisVPL: Probabilistic Discriminative Visual Part Learning for Image Classification,
MultMedMag(25), No. 4, October 2018, pp. 34-45.
IEEE DOI 1901
Visualization, Detectors, Probabilistic logic, Training, Feature extraction, Image classification, Computational modeling, image BibRef

Chai, J.[Jing], Ding, X.H.[Xing-Hao], Chen, H.T.[Hong-Tao], Li, T.Y.[Ting-Yu],
Multiple-instance discriminant analysis,
PR(47), No. 7, 2014, pp. 2517-2531.
Elsevier DOI 1404
Multiple-instance learning BibRef

Li, Z.[Zhan], Geng, G.H.[Guo-Hua], Feng, J.[Jun], Peng, J.Y.[Jin-Ye], Wen, C.[Chao], Liang, J.L.[Jun-Li],
Multiple instance learning based on positive instance selection and bag structure construction,
PRL(40), No. 1, 2014, pp. 19-26.
Elsevier DOI 1403
Multiple instance learning (MIL) BibRef

Cheplygina, V.[Veronika], Tax, D.M.J.[David M.J.], Loog, M.[Marco],
Multiple instance learning with bag dissimilarities,
PR(48), No. 1, 2015, pp. 264-275.
Elsevier DOI 1410
Multiple instance learning BibRef

Cheplygina, V.[Veronika], Tax, D.M.J.[David M.J.], Loog, M.[Marco],
On classification with bags, groups and sets,
PRL(59), No. 1, 2015, pp. 11-17.
Elsevier DOI 1505
Multiple instance learning BibRef

Alpaydin, E.[Ethem], Cheplygina, V.[Veronika], Loog, M.[Marco], Tax, D.M.J.[David M.J.],
Single- vs. multiple-instance classification,
PR(48), No. 9, 2015, pp. 2831-2838.
Elsevier DOI 1506
Classification BibRef

Carbonneau, M.A.[Marc-André], Granger, E.[Eric], Raymond, A.J.[Alexandre J.], Gagnon, G.[Ghyslain],
Robust multiple-instance learning ensembles using random subspace instance selection,
PR(58), No. 1, 2016, pp. 83-99.
Elsevier DOI 1606
BibRef
And: A1, A2, A4, Only:
Witness identification in multiple instance learning using random subspaces,
ICPR16(3639-3644)
IEEE DOI 1705
Classification algorithms, Clustering algorithms, Knowledge discovery, Prototypes, Robustness, Standards, Support vector machines, Knowledge Discovery, Multiple Instance Learning, Random Subspace Methods, Witness, Identification BibRef

Carbonneau, M.A.[Marc-André], Granger, E.[Eric], Gagnon, G.[Ghyslain],
Score thresholding for accurate instance classification in multiple instance learning,
IPTA16(1-6)
IEEE DOI 1703
learning (artificial intelligence) BibRef

Ding, X., Li, B., Xiong, W., Guo, W., Hu, W., Wang, B.,
Multi-Instance Multi-Label Learning Combining Hierarchical Context and its Application to Image Annotation,
MultMed(18), No. 8, August 2016, pp. 1616-1627.
IEEE DOI 1608
Automation BibRef

Qiao, M.Y.[Mao-Ying], Liu, L.[Liu], Yu, J.[Jun], Xu, C.[Chang], Tao, D.C.[Da-Cheng],
Diversified dictionaries for multi-instance learning,
PR(64), No. 1, 2017, pp. 407-416.
Elsevier DOI 1701
Multi-instance learning BibRef

Xiao, Y.S.[Yan-Shan], Liu, B.[Bo], Hao, Z.F.[Zhi-Feng],
A Sphere-Description-Based Approach for Multiple-Instance Learning,
PAMI(39), No. 2, February 2017, pp. 242-257.
IEEE DOI 1702
Internet BibRef

Wang, J.J.Y.[Jim Jing-Yan], Tsang, I.W.H.[Ivor Wai-Hung], Cui, X.F.[Xue-Feng], Lu, Z.[Zhiwu], Gao, X.[Xin],
Multi-instance dictionary learning via multivariate performance measure optimization,
PR(66), No. 1, 2017, pp. 448-459.
Elsevier DOI 1704
Multi-instance learning BibRef

Tang, P.[Peng], Wang, X.G.[Xing-Gang], Feng, B.[Bin], Liu, W.Y.[Wen-Yu],
Learning Multi-Instance Deep Discriminative Patterns for Image Classification,
IP(26), No. 7, July 2017, pp. 3385-3396.
IEEE DOI 1706
Feature extraction, Image representation, Neural networks, Semantics, Stochastic processes, Support vector machines, Training, Image classification, deep convolutional neural networks, discriminative patterns, multi-instance learning, stochastic gradient decent. BibRef

Tang, P.[Peng], Wang, X.G.[Xing-Gang], Bai, X.[Xiang], Liu, W.Y.[Wen-Yu],
Multiple Instance Detection Network with Online Instance Classifier Refinement,
CVPR17(3059-3067)
IEEE DOI 1711
Benchmark testing, Detectors, Manifolds, Object detection, Proposals, Streaming media, Training BibRef

Wu, J.X.[Jian-Xin], Bai, X.[Xiang], Loog, M.[Marco], Roli, F.[Fabio], Zhou, Z.H.[Zhi-Hua],
Editorial of the Special Issue on Multi-instance Learning in Pattern Recognition and Vision,
PR(71), No. 1, 2017, pp. 444-445.
Elsevier DOI 1707
BibRef

Xu, D.K.[Dong-Kuan], Wu, J.[Jia], Li, D.[Dewei], Tian, Y.J.[Ying-Jie], Zhu, X.Q.[Xing-Quan], Wu, X.D.[Xin-Dong],
SALE: Self-adaptive LSH encoding for multi-instance learning,
PR(71), No. 1, 2017, pp. 460-482.
Elsevier DOI 1707
Multi-instance learning BibRef

Verma, M.[Mridula], Shukla, K.K.,
A new accelerated proximal gradient technique for regularized multitask learning framework,
PRL(95), No. 1, 2017, pp. 98-103.
Elsevier DOI 1708
Multitask learning BibRef

Liu, X.[Xu], Jiao, L.C.[Li-Cheng], Zhao, J.Q.[Jia-Qi], Zhao, J.[Jin], Zhang, D.[Dan], Liu, F.[Fang], Yang, S.Y.[Shu-Yuan], Tang, X.[Xu],
Deep Multiple Instance Learning-Based Spatial-Spectral Classification for PAN and MS Imagery,
GeoRS(56), No. 1, January 2018, pp. 461-473.
IEEE DOI 1801
Convolution, Feature extraction, Machine learning, Neural networks, Spatial resolution, Deep learning, feature fusion, multiple instance learning BibRef

Carbonneau, M.A.[Marc-André], Cheplygina, V.[Veronika], Granger, E.[Eric], Gagnon, G.[Ghyslain],
Multiple instance learning: A survey of problem characteristics and applications,
PR(77), 2018, pp. 329-353.
Elsevier DOI 1802
Multiple instance learning, Weakly supervised learning, Classification, Multi-instance learning, Computer vision, Drug activity prediction BibRef

Song, L., Liu, J., Qian, B., Sun, M., Yang, K., Sun, M., Abbas, S.,
A Deep Multi-Modal CNN for Multi-Instance Multi-Label Image Classification,
IP(27), No. 12, December 2018, pp. 6025-6038.
IEEE DOI 1810
Visualization, Task analysis, Correlation, Feature extraction, Computer science, Electronic mail, Sun, CNN, context information BibRef

Asif, A.[Amina], Minhas, F.U.A.[Fayyaz Ul_Amir Afsar],
An embarrassingly simple approach to neural multiple instance classification,
PRL(128), 2019, pp. 474-479.
Elsevier DOI 1912
Machine Learning, Classification, Multiple Instance Learning, Neural Networks BibRef

Li, Z., Xu, K., Xie, J., Bi, Q., Qin, K.,
Deep Multiple Instance Convolutional Neural Networks for Learning Robust Scene Representations,
GeoRS(58), No. 5, May 2020, pp. 3685-3702.
IEEE DOI 2005
Convolutional neural network (CNN), multiple instance learning (MIL), scene classification, scene representation BibRef

Bhattacharjee, K.[Kamanasish], Pant, M.[Millie], Zhang, Y.D.[Yu-Dong], Satapathy, S.C.[Suresh Chandra],
Multiple Instance Learning with Genetic Pooling for medical data analysis,
PRL(133), 2020, pp. 247-255.
Elsevier DOI 2005
Multiple Instance Learning (MIL), Genetic Algorithm (GA), Pooling, Neural network BibRef


Yuan, L., Wen, X., Xu, H., Zhao, L.,
Multiple- Instance Learning with Empirical Estimation Guided Instance Selection,
ICPR18(770-775)
IEEE DOI 1812
Training, Prototypes, Estimation, Support vector machines, Standards, Supervised learning, Reactive power BibRef

Kandemir, M.[Melih], Haussmann, M.[Manuel], Diego, F.[Ferran], Rajamani, K.[Kumar], Van Der Laak, J.[Jeroen], Hamprecht, F.[Fred],
Variational Weakly Supervised Gaussian Processes,
BMVC16(xx-yy).
HTML Version. 1805
Multiple instance learning (MIL) BibRef

Dong, M., Pang, K., Wu, Y., Xue, J.H., Hospedales, T., Ogasawara, T.,
Transferring CNNS to multi-instance multi-label classification on small datasets,
ICIP17(1332-1336)
IEEE DOI 1803
Convolution, Feature extraction, Image annotation, Logistics, Semantics, Task analysis, Training, CNN, Multi-instance, Multi-label, Transfer Learning BibRef

Haußmann, M., Hamprecht, F.A., Kandemir, M.,
Variational Bayesian Multiple Instance Learning with Gaussian Processes,
CVPR17(810-819)
IEEE DOI 1711
Gaussian processes, Object detection, Pipelines, Predictive models, Proposals, Supervised learning, Training BibRef

Karem, A., Frigui, H.,
Multiple Instance Learning with multiple positive and negative target concepts,
ICPR16(474-479)
IEEE DOI 1705
Clustering algorithms, Correlation, Noise measurement, Optimization, Standards, Support, vector, machines BibRef

Venkatesan, R., Chandakkar, P.S., Li, B.,
Simpler Non-Parametric Methods Provide as Good or Better Results to Multiple-Instance Learning,
ICCV15(2605-2613)
IEEE DOI 1602
Benchmark testing BibRef

Wang, X., Zhu, Z., Yao, C., Bai, X.,
Relaxed Multiple-Instance SVM with Application to Object Discovery,
ICCV15(1224-1232)
IEEE DOI 1602
Image edge detection BibRef

Sikka, K.[Karan], Giri, R.[Ritwik], Bartlett, M.[Marian],
Joint Clustering and Classification for Multiple Instance Learning,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Yuan, L.M.[Li-Ming], Zhao, L.[Lu], Xu, H.X.[Hai-Xia],
Multi-instance learning via instance-based and bag-based representation transformations,
ICIP15(2771-2775)
IEEE DOI 1512
Multi-instance learning BibRef

Rastegari, M.[Mohammad], Hajishirzi, H.[Hannaneh], Farhadi, A.[Ali],
Discriminative and consistent similarities in instance-level Multiple Instance Learning,
CVPR15(740-748)
IEEE DOI 1510
BibRef

Hajimirsadeghi, H.[Hossein], Yan, W.[Wang], Vahdat, A.[Arash], Mori, G.[Greg],
Visual recognition by counting instances: A multi-instance cardinality potential kernel,
CVPR15(2596-2605)
IEEE DOI 1510
BibRef

Hoffman, J.[Judy], Pathak, D.[Deepak], Darrell, T.J.[Trevor J.], Saenko, K.[Kate],
Detector discovery in the wild: Joint multiple instance and representation learning,
CVPR15(2883-2891)
IEEE DOI 1510
BibRef

Wu, J.J.[Jia-Jun], Yu, Y.[Yinan], Huang, C.[Chang], Yu, K.[Kai],
Deep multiple instance learning for image classification and auto-annotation,
CVPR15(3460-3469)
IEEE DOI 1510
BibRef

Li, W.X.[Wei-Xin], Vasconcelos, N.M.[Nuno M.],
Multiple instance learning for soft bags via top instances,
CVPR15(4277-4285)
IEEE DOI 1510
BibRef

Yoon, J.[Jaesik], Choi, J.H.[Jin-Ho], Yoo, C.D.[Chang D.],
A hierarchical-structured dictionary learning for image classification,
ICIP14(155-159)
IEEE DOI 1502
Algorithm design and analysis BibRef

Shrivastava, A.[Ashish], Pillai, J.K.[Jaishanker K.], Patel, V.M.[Vishal M.], Chellappa, R.[Rama],
Dictionary-based multiple instance learning,
ICIP14(160-164)
IEEE DOI 1502
Computer vision BibRef

Fukui, T.[Takayuki], Wada, T.[Toshikazu],
Commonality Preserving Multiple Instance Clustering Based on Diverse Density,
FSLCV14(III: 322-335).
Springer DOI 1504
BibRef
Earlier:
Commonality Preserving Image-Set Clustering Based on Diverse Density,
ISVC14(I: 258-269).
Springer DOI 1501
BibRef

Ali, K.[Karim], Saenko, K.[Kate],
Confidence-Rated Multiple Instance Boosting for Object Detection,
CVPR14(2433-2440)
IEEE DOI 1409
Gradient Boosting; Mutliple Instance Learning; Object Detection BibRef

Wang, Y.Y.[Ying-Ying], Zhang, C.[Chun], Wang, Z.H.[Zhi-Hua],
Rate distortion Multiple Instance Learning for image classification,
ICIP13(3235-3238)
IEEE DOI 1402
Image Classification; Multiple Instance Learning; Rate Distortion BibRef

Zhao, H.F.[Hai-Feng], Cheng, J.[Jun], Jiang, J.[Jun], Tao, D.C.[Da-Cheng],
Multiple instance learning via distance metric optimization,
ICIP13(2617-2621)
IEEE DOI 1402
MILES BibRef

Cheplygina, V.[Veronika], Tax, D.M.J.[David M. J.], Loog, M.[Marco],
Class-Dependent Dissimilarity Measures for Multiple Instance Learning,
SSSPR12(602-610).
Springer DOI 1211
BibRef

Antic, B.[Borislav], Ommer, B.[Björn],
Robust Multiple-Instance Learning with Superbags,
ACCV12(II:242-255).
Springer DOI 1304
Alternate between learn classifier with missing labels, learn missing labels with a classifier. BibRef

Brossi, S.D., Bradley, A.P.,
A Comparison of Multiple Instance and Group Based Learning,
DICTA12(1-8).
IEEE DOI 1303
BibRef

Ngo, T.D.[Thanh Duc], Le, D.D.[Duy-Dinh], Satoh, S.[Shin'ichi],
Improving Image Categorization by Using Multiple Instance Learning with Spatial Relation,
CIAP11(I: 108-117).
Springer DOI 1109
BibRef

Kang, F.[Feng], Naphade, M.R.[Milind R.],
A Generalized Multiple Instance Learning Algorithm for Iterative Distillation and Cross-Granular Propagation of Video Annotations,
ICIP07(II: 205-208).
IEEE DOI 0709
BibRef
Earlier:
A Generalized Multiple Instance Learning Algorithm with Multiple Selection Strategies for Cross Granular Learning,
ICIP06(3213-3216).
IEEE DOI 0610
BibRef

Du, R.[Ruo], Wang, S.[Sheng], Wu, Q.A.[Qi-Ang], He, X.J.[Xiang-Jian],
Learn Concepts in Multiple-Instance Learning with Diverse Density Framework Using Supervised Mean Shift,
DICTA10(643-648).
IEEE DOI 1012
BibRef

Wu, D.[Dijia], Boyer, K.L.[Kim L.],
Resilient Subclass Discriminant Analysis,
ICCV09(389-396).
IEEE DOI 0909
BibRef

Wu, D.[Dijia], Bi, J.[Jinbo], Boyer, K.L.[Kim L.],
A min-max framework of cascaded classifier with multiple instance learning for computer aided diagnosis,
CVPR09(1359-1366).
IEEE DOI 0906
BibRef

Pao, H.T.[Hsiao T.], Xu, Y.Y.[Yeong Y.], Chuang, S.C.[Shun C.], Fu, H.C.[Hsin C.],
Image Classification and Indexing by EM Based Multiple-Instance Learning,
Visual07(146-153).
Springer DOI 0706
BibRef

Maron, O.[Oded], Ratan, A.L.[Aparna L.],
Multiple-Instance Learning for Natural Scene Classification,
DARPA98(1031-1036). BibRef 9800

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Learning Model Descriptions .


Last update:Sep 14, 2020 at 15:32:18