Sharp analysis of low-rank kernel matrix approximations, Conference on Learning Theory, pp.185-209, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-00723365
Non-asymptotic analysis of stochastic approximation algorithms for machine learning, Adv. NIPS, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00608041
Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n), Advances in Neural Information Processing Systems (NIPS), 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-00831977
Fast kernel classifiers with online and active learning, Journal of Machine Learning Research, vol.6, pp.1579-1619, 2005. ,
URL : https://hal.archives-ouvertes.fr/hal-00752361
Optimization methods for large-scale machine learning, 2016. ,
Optimal rates for the regularized least-squares algorithm, Foundations of Computational Mathematics, vol.7, issue.3, pp.331-368, 2007. ,
Nonparametric stochastic approximation with large step-sizes, Ann. Statist, vol.44, issue.4, pp.1363-1399, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01053831
Bridging the gap between constant step size stochastic gradient descent and markov chains, 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-01565514
Markov chain Monte Carlo in practice, 1995. ,
Deep Learning, 2016. ,
Negative binomial regression, 2011. ,
Probabilistic Graphical Models: Principles and Techniques-Adaptive Computation and Machine Learning, 2009. ,
Conditional random fields: Probabilistic models for segmenting and labeling sequence data, Proc. ICML, 2001. ,
UCI machine learning repository, 2013. ,
Generalized linear models, European Journal of Operational Research, vol.16, issue.3, pp.285-292, 1984. ,
Markov chains and stochastic stability, 1993. ,
Machine Learning: A Probabilistic Perspective, 2012. ,
Acceleration of stochastic approximation by averaging, SIAM Journal on Control and Optimization, vol.30, issue.4, pp.838-855, 1992. ,
Gaussian Processes for Machine Learning, 2006. ,
Falkon: An optimal large scale kernel method, Advances in Neural Information Processing Systems, pp.3891-3901, 2017. ,
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and beyond, 2001. ,
Kernel Methods for Pattern Analysis, 2004. ,
Injective hilbert space embeddings of probability measures, Proc. COLT, 2008. ,
Using the nyström method to speed up kernel machines, Advances in neural information processing systems, pp.682-688, 2001. ,
Sketching as a tool for numerical linear algebra, Foundations and Trends R in Theoretical Computer Science, vol.10, issue.1-2, pp.1-157, 2014. ,