Stochastic Compositional Gradient Descent: Algorithms for Minimizing Compositions of Expected-Value Functions

14 November 2014

Papers citing "Stochastic Compositional Gradient Descent: Algorithms for Minimizing Compositions of Expected-Value Functions"

10 / 10 papers shown

Title
Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning Kuan-Fu Ding Jingyang Li Kim-Chuan Toh 101 8 0 26 Jun 2023
Stochastic Compositional Optimization with Compositional Constraints Shuoguang Yang Wei You Zhe Zhang Ethan X. Fang 70 3 0 09 Sep 2022
Sinkhorn Distributionally Robust Optimization Jie Wang Rui Gao Yao Xie 127 39 0 24 Sep 2021
Statistical Estimation of Composite Risk Functionals and Risk Optimization Problems Darinka Dentcheva S. Penev A. Ruszczynski 56 71 0 10 Apr 2015
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 162 576 0 08 Dec 2012
Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization Alexander Rakhlin Ohad Shamir Karthik Sridharan 182 769 0 26 Sep 2011
Variable selection in nonparametric additive models Jian Huang J. Horowitz Fengrong Wei 270 549 0 20 Oct 2010
Information-theoretic lower bounds on the oracle complexity of stochastic convex optimization Alekh Agarwal Peter L. Bartlett Pradeep Ravikumar Martin J. Wainwright 212 251 0 03 Sep 2010
High-dimensional analysis of semidefinite relaxations for sparse principal components Arash A. Amini Martin J. Wainwright 176 314 0 27 Mar 2008
Sparse Additive Models Pradeep Ravikumar John D. Lafferty Han Liu Larry A. Wasserman 506 573 0 28 Nov 2007