暂无分享,去创建一个
[1] Ohad Shamir,et al. Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization , 2011, ICML.
[2] Yuan Yao,et al. Online Learning as Stochastic Approximation of Regularization Paths: Optimality and Almost-Sure Convergence , 2011, IEEE Transactions on Information Theory.
[3] Martin Zinkevich,et al. Online Convex Programming and Generalized Infinitesimal Gradient Ascent , 2003, ICML.
[4] M. Fathi,et al. Transport-Entropy inequalities and deviation estimates for stochastic approximation schemes , 2013, 1301.7740.
[5] Thomas P. Hayes,et al. Stochastic Linear Optimization under Bandit Feedback , 2008, COLT.
[6] Elad Hazan,et al. An optimal algorithm for stochastic strongly-convex optimization , 2010, 1006.2425.
[7] Wei Chu,et al. A contextual-bandit approach to personalized news article recommendation , 2010, WWW '10.
[8] Mark W. Schmidt,et al. A Stochastic Gradient Method with an Exponential Convergence Rate for Finite Training Sets , 2012, NIPS.
[9] Shai Shalev-Shwartz,et al. Stochastic dual coordinate ascent methods for regularized loss , 2012, J. Mach. Learn. Res..
[10] John N. Tsitsiklis,et al. Linearly Parameterized Bandits , 2008, Math. Oper. Res..
[11] Eric Moulines,et al. Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning , 2011, NIPS.
[12] S. Menozzi,et al. Concentration bounds for stochastic approximations , 2012, 1204.3730.
[13] Tong Zhang,et al. Accelerating Stochastic Gradient Descent using Predictive Variance Reduction , 2013, NIPS.