Learning from Multiple Partially Observed Views -an Application to Multilingual Text Categorization, NIPS, 2009. ,
URL : https://hal.archives-ouvertes.fr/hal-01297947
Combining labeled and unlabeled data with co-training, Proceedings of the eleventh annual conference on Computational learning theory , COLT' 98, pp.92-100, 1998. ,
DOI : 10.1145/279943.279962
URL : http://l2r.cs.uiuc.edu/~danr/Teaching/CS598-05/Papers/cotraining.pdf
The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming, USSR Computational Mathematics and Mathematical Physics, vol.7, issue.3, pp.200-217, 1967. ,
DOI : 10.1016/0041-5553(67)90040-7
Multi-view Generative Adversarial Networks, ECML-PKDD, pp.175-188, 2017. ,
DOI : 10.1016/j.patcog.2010.12.011
URL : http://arxiv.org/pdf/1611.02019
Logistic regression, adaboost and bregman distances, Machine Learning, vol.48, issue.1/3, pp.253-285, 2002. ,
DOI : 10.1023/A:1013912006537
Generalized Iterative Scaling for Log-Linear Models, The Annals of Mathematical Statistics, pp.1470-1480, 1972. ,
DOI : 10.1214/aoms/1177692379
URL : http://doi.org/10.1214/aoms/1177692379
Inducing features of random fields, IEEE TPAMI, vol.19, issue.4, pp.380-393, 1997. ,
Two view learning: Svm-2k, theory and practice, NIPS, pp.355-362, 2006. ,
Multiple kernel learning algorithms, JMLR, vol.12, pp.2211-2268, 2011. ,
Multi-view Metric Learning in Vector-valued Kernel Spaces, AISTATS, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01736068
Boosting Classifiers built from Different Subsets of Features, Fundamenta Informaticae, vol.94, pp.1-21, 2009. ,
URL : https://hal.archives-ouvertes.fr/hal-00403242
A boosting approach to multiview classification with cooperation, 2011. ,
Additive models, boosting, and inference for generalized divergences, Proceedings of the twelfth annual conference on Computational learning theory , COLT '99, pp.125-133, 1999. ,
DOI : 10.1145/307400.307422
URL : http://www.cs.cmu.edu/Groups/reinforcement/mosaic/talks-1999/99-11-15.paper.ps.gz
Gradient-based learning applied to document recognition, Proceedings of the IEEE, pp.2278-2324, 1998. ,
DOI : 10.1109/5.726791
URL : http://www.cs.berkeley.edu/~daf/appsem/Handwriting/papers/00726791.pdf
Scikit-learn: Machine learning in Python, JMLR, vol.12, pp.2825-2830, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00650905
ShareBoost: Boosting for Multi-view Learning with Performance Guarantees, ECML-PKDD, pp.597-612, 2011. ,
DOI : 10.1016/S0893-6080(05)80023-1
Multiview Boosting With Information Propagation for Classification, IEEE Transactions on Neural Networks and Learning Systems, vol.29, issue.3, pp.1-13, 2017. ,
DOI : 10.1109/TNNLS.2016.2637881
Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation, J. of Machine Learning Technologies, vol.1, issue.2, pp.37-63, 2011. ,
An RKHS for multi-view learning and manifold co-regularization, Proceedings of the 25th international conference on Machine learning, ICML '08, pp.976-983, 2008. ,
DOI : 10.1145/1390156.1390279
URL : http://icml2008.cs.helsinki.fi/papers/641.pdf
Early versus late fusion in semantic video analysis, Proceedings of the 13th annual ACM international conference on Multimedia , MULTIMEDIA '05, pp.399-402, 2005. ,
DOI : 10.1145/1101149.1101236
URL : http://staff.science.uva.nl/~cgmsnoek/pub/snoek-earlylate-acm2005.pdf
A survey of multi-view machine learning, Neural Computing and Applications, vol.43, issue.7-8, pp.2031-2038, 2013. ,
DOI : 10.1016/j.patcog.2010.04.004
The Nature of Statistical Learning Theory, 1999. ,
Multi-view adaboost for multilingual subjectivity analysis, In COLING, pp.2851-2866, 2012. ,
Large-Margin Multi-ViewInformation Bottleneck, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.36, issue.8, pp.1559-1572, 2014. ,
DOI : 10.1109/TPAMI.2013.2296528
Multi-View Learning With Incomplete Views, IEEE Transactions on Image Processing, vol.24, issue.12, pp.5812-5825, 2015. ,
DOI : 10.1109/TIP.2015.2490539
Co-Labeling for Multi-View Weakly Labeled Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.38, issue.6, pp.1113-1125, 2016. ,
DOI : 10.1109/TPAMI.2015.2476813
An Algorithm on Multi-View Adaboost, ICONIP, 2010. ,
DOI : 10.1145/1390156.1390203
A novel ensemble construction method for multi-view data using random cross-view correlation between within-class examples, Pattern Recognition, vol.44, issue.6, pp.1162-1171, 2011. ,
DOI : 10.1016/j.patcog.2010.12.011
URL : http://parnec.nuaa.edu.cn/zhangdq/J-11-PR11.pdf