Natural Gradient Works Efficiently in Learning, Neural Computation, vol.37, issue.2, pp.251-276, 1998. ,
DOI : 10.1103/PhysRevLett.76.2188
Convexity, Classification, and Risk Bounds, Journal of the American Statistical Association, vol.101, issue.473, pp.138-156, 2006. ,
DOI : 10.1198/016214505000000907
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.3497
Sgd-qn: Careful quasi-newton stochastic gradient descent, J. Mach. Learn. Res, vol.10, pp.1737-1754, 2007. ,
URL : https://hal.archives-ouvertes.fr/hal-00750911
Erratum: Sgdqn is less careful than expected, J. Mach. Learn. Res, vol.11, pp.2229-2240, 2003. ,
URL : https://hal.archives-ouvertes.fr/hal-00750268
The tradeoffs of large scale learning, NIPS*20, pp.161-168, 2008. ,
ImageNet: A Large- Scale Hierarchical Image Database, CVPR'09, 2009. ,
A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting, Journal of Computer and System Sciences, vol.55, issue.1, pp.119-139, 1997. ,
DOI : 10.1006/jcss.1997.1504
Caltech-256 object category dataset, 2007. ,
Optimizing search engines using clickthrough data, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '02, pp.133-142, 2002. ,
DOI : 10.1145/775047.775067
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.3161
Applications of strong convexity? strong smoothness duality to learning with matrices, p.18, 2009. ,
Building support vector machines with reduced classifier complexity, JMLR, vol.7, issue.7 2, pp.1493-1515, 2006. ,
Metric Learning for Large Scale Image Classification: Generalizing to New Classes at Near-Zero Cost, Procs of the 12 th ECCV, 2012. ,
DOI : 10.1007/978-3-642-33709-3_35
URL : https://hal.archives-ouvertes.fr/hal-00722313
On the efficient minimization of classification-calibrated surrogates, NIPS*21, pp.1201-1208, 2008. ,
Towards good practice in largescale learning for image classification, CVPR'12, pp.3482-3489, 2007. ,
URL : https://hal.archives-ouvertes.fr/hal-00690014
Improving the Fisher Kernel for Large-Scale Image Classification, Procs of the 11 th ECCV, pp.143-156, 2010. ,
DOI : 10.1007/978-3-642-15561-1_11
URL : https://hal.archives-ouvertes.fr/inria-00548630
A Stochastic Quasi-Newton Method for Online Convex Optimization, AISTATS'07, pp.436-443, 2007. ,
Pegasos, Proceedings of the 24th international conference on Machine learning, ICML '07, pp.807-814, 2007. ,
DOI : 10.1145/1273496.1273598
Statistical Learning Theory, 1998. ,
Composite multiclass losses, NIPS*24, pp.1224-1232, 2011. ,
Locality-constrained Linear Coding for image classification, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.3360-3367, 2010. ,
DOI : 10.1109/CVPR.2010.5540018
Wsabie: Scaling up to large vocabulary image annotation, IJCAI'11, pp.2764-2770, 2011. ,
SUN database: Large-scale scene recognition from abbey to zoo, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.3485-3492, 2010. ,
DOI : 10.1109/CVPR.2010.5539970
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.469.2228
Solving large scale linear prediction problems using stochastic gradient descent algorithms, Twenty-first international conference on Machine learning , ICML '04, pp.116-123, 2004. ,
DOI : 10.1145/1015330.1015332