Optimal algorithms for online convex optimization with multipoint bandit feedback, Proc. COLT, 2010. ,
Stochastic Convex Optimization with Bandit Feedback, SIAM Journal on Optimization, vol.23, issue.1, pp.188-212, 2013. ,
DOI : 10.1137/110850827
Self-concordant analysis for logistic regression, Electronic Journal of Statistics, vol.4, issue.0, pp.384-414, 2010. ,
DOI : 10.1214/09-EJS521
URL : https://hal.archives-ouvertes.fr/hal-00426227
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), Adv. NIPS, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-00831977
Convex optimization: Algorithms and complexity. Foundations and Trends, Machine Learning, pp.231-357, 2015. ,
DOI : 10.1561/2200000050
URL : http://arxiv.org/abs/1405.4980
Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems, Machine Learning, pp.1-122, 2012. ,
DOI : 10.1561/2200000024
Lower Rate of Convergence for Locating a Maximum of a Function, The Annals of Statistics, vol.16, issue.3, pp.1330-1334, 1988. ,
DOI : 10.1214/aos/1176350965
Accelerated randomized stochastic optimization, The Annals of Statistics, vol.31, issue.4, pp.1260-1281, 2003. ,
DOI : 10.1214/aos/1059655913
Optimal Rates for Zero-Order Convex Optimization: The Power of Two Function Evaluations, IEEE Transactions on Information Theory, vol.61, issue.5, 2013. ,
DOI : 10.1109/TIT.2015.2409256
Stochastic Approximation of Minima with Improved Asymptotic Speed, The Annals of Mathematical Statistics, vol.38, issue.1, pp.191-200, 1967. ,
DOI : 10.1214/aoms/1177699070
Online convex optimization in the bandit setting: gradient descent without a gradient, Proc. Symposium on Discrete algorithms (SODA). Society for Industrial and Applied Mathematics, 2005. ,
Bandit convex optimization: Towards tight bounds, Adv. NIPS, 2014. ,
Logistic regression: Tight bounds for stochastic and online optimization, Proc. Conference On Learning Theory (COLT), 2014. ,
Accelerated gradient methods for stochastic optimization and online learning, Advances in Neural Information Processing Systems, 2009. ,
Learning exponential families in highdimensions: Strong convexity and sparsity, pp.54-56, 2009. ,
Stochastic approximation and Recursive Algorithms and Applications, 2003. ,
An optimal method for stochastic composite optimization, Mathematical Programming, pp.365-397, 2012. ,
DOI : 10.1007/s10107-010-0434-y
Validation analysis of mirror descent stochastic approximation method, Mathematical Programming, vol.24, issue.2, pp.425-458, 2012. ,
DOI : 10.1007/s10107-011-0442-6
On zeroth-order stochastic convex optimization via random walks, 2014. ,
Problem complexity and method efficiency in optimization, 1983. ,
Interior point polynomial time methods in convex programming, Lecture Notes, 2004. ,
Introductory Lectures on Convex Optimization, of Applied Optimization, 2004. ,
DOI : 10.1007/978-1-4419-8853-9
Random Gradient-Free Minimization of Convex Functions, Foundations of Computational Mathematics, vol.66, issue.2, 2011. ,
DOI : 10.1007/s10208-015-9296-2
Optimal order of accuracy of search algorithms in stochastic optimization, Problemy Peredachi Informatsii, vol.26, issue.2, pp.45-53, 1990. ,