Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization

19 June 2013

Papers citing "Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization"

28 / 28 papers shown

Title
Online Learning Under A Separable Stochastic Approximation Framework Min Gan Xiang-Xiang Su Guang-yong Chen Jing Chen 28 0 0 12 May 2023
Two Losses Are Better Than One: Faster Optimization Using a Cheaper Proxy Blake E. Woodworth Konstantin Mishchenko Francis R. Bach 44 6 0 07 Feb 2023
Target-based Surrogates for Stochastic Optimization J. Lavington Sharan Vaswani Reza Babanezhad Mark Schmidt Nicolas Le Roux 57 5 0 06 Feb 2023
Convex Clustering through MM: An Efficient Algorithm to Perform Hierarchical Clustering Daniel J. W. Touw P. Groenen Y. Terada 26 3 0 03 Nov 2022
Statistical inference of random graphs with a surrogate likelihood function Dingbo Wu Fangzheng Xie 20 2 0 04 Jul 2022
Supervised Dictionary Learning with Auxiliary Covariates Joo-Hyun Lee Hanbaek Lyu W. Yao 30 1 0 14 Jun 2022
Large-scale Optimization of Partial AUC in a Range of False Positive Rates Yao Yao Qihang Lin Tianbao Yang 38 16 0 03 Mar 2022
On Almost Sure Convergence Rates of Stochastic Gradient Methods Jun Liu Ye Yuan 21 36 0 09 Feb 2022
Adaptive Mixing of Auxiliary Losses in Supervised Learning D. Sivasubramanian Ayush Maheshwari Pradeep Shenoy A. Prathosh Ganesh Ramakrishnan 29 5 0 07 Feb 2022
MIO : Mutual Information Optimization using Self-Supervised Binary Contrastive Learning Siladittya Manna Umapada Pal Saumik Bhattacharya SSL 35 1 0 24 Nov 2021
Two-Stage Stochastic Optimization via Primal-Dual Decomposition and Deep Unrolling An Liu Rui Yang Tony Q.S. Quek Min-Jian Zhao 27 12 0 05 May 2021
Fast and Secure Distributed Nonnegative Matrix Factorization Yuqiu Qian Conghui Tan Danhao Ding Hui Li N. Mamoulis 33 13 0 07 Sep 2020
NoPeek: Information leakage reduction to share activations in distributed deep learning Praneeth Vepakomma Abhishek Singh O. Gupta Ramesh Raskar MIACV FedML 26 84 0 20 Aug 2020
Truncated Inference for Latent Variable Optimization Problems: Application to Robust Estimation and Learning Christopher Zach Huu Le 33 4 0 12 Mar 2020
Online matrix factorization for Markovian data and applications to Network Dictionary Learning Hanbaek Lyu Deanna Needell Laura Balzano 29 26 0 05 Nov 2019
Distributed Inexact Successive Convex Approximation ADMM: Analysis-Part I Sandeep Kumar K. Rajawat Daniel P. Palomar 24 4 0 21 Jul 2019
Screening Rules for Lasso with Non-Convex Sparse Regularizers A. Rakotomamonjy Gilles Gasso Joseph Salmon 36 24 0 16 Feb 2019
Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence Yi Tian Xu Qi Qi Qihang Lin Rong Jin Tianbao Yang 37 41 0 28 Nov 2018
On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes Xiaoyun Li Francesco Orabona 40 291 0 21 May 2018
Bayesian Projected Calibration of Computer Models Fangzheng Xie Yanxun Xu 8 34 0 03 Mar 2018
Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method Mark Eisen Aryan Mokhtari Alejandro Ribeiro 27 16 0 22 May 2017
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite-Sum Structure A. Bietti Julien Mairal 47 36 0 04 Oct 2016
Online Categorical Subspace Learning for Sketching Big Data with Misses Yanning Shen Morteza Mardani G. Giannakis 21 16 0 27 Sep 2016
Online Nonnegative Matrix Factorization with General Divergences Renbo Zhao Vincent Y. F. Tan Huan Xu 26 29 0 30 Jul 2016
Online Nonnegative Matrix Factorization with Outliers Renbo Zhao Vincent Y. F. Tan 27 47 0 10 Apr 2016
Sparse Modeling for Image and Vision Processing Julien Mairal Francis R. Bach Jean Ponce VLM 47 488 0 12 Nov 2014
Block stochastic gradient iteration for convex and nonconvex optimization Yangyang Xu W. Yin 28 134 0 12 Aug 2014
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning Julien Mairal 79 317 0 18 Feb 2014