Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
1306.4650
Cited By
Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization
19 June 2013
Julien Mairal
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization"
22 / 22 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
42
6
0
07 Feb 2023
Convex Clustering through MM: An Efficient Algorithm to Perform Hierarchical Clustering
Daniel J. W. Touw
P. Groenen
Y. Terada
15
3
0
03 Nov 2022
Supervised Dictionary Learning with Auxiliary Covariates
Joo-Hyun Lee
Hanbaek Lyu
W. Yao
30
1
0
14 Jun 2022
On Almost Sure Convergence Rates of Stochastic Gradient Methods
Jun Liu
Ye Yuan
21
36
0
09 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
20
12
0
05 May 2021
Fast and Secure Distributed Nonnegative Matrix Factorization
Yuqiu Qian
Conghui Tan
Danhao Ding
Hui Li
N. Mamoulis
30
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
21
84
0
20 Aug 2020
Truncated Inference for Latent Variable Optimization Problems: Application to Robust Estimation and Learning
Christopher Zach
Huu Le
23
4
0
12 Mar 2020
Online matrix factorization for Markovian data and applications to Network Dictionary Learning
Hanbaek Lyu
Deanna Needell
Laura Balzano
27
26
0
05 Nov 2019
Distributed Inexact Successive Convex Approximation ADMM: Analysis-Part I
Sandeep Kumar
K. Rajawat
Daniel P. Palomar
19
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
R. L. Jin
Tianbao Yang
37
41
0
28 Nov 2018
On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes
Xiaoyun Li
Francesco Orabona
40
290
0
21 May 2018
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite-Sum Structure
A. Bietti
Julien Mairal
44
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
23
29
0
30 Jul 2016
Online Nonnegative Matrix Factorization with Outliers
Renbo Zhao
Vincent Y. F. Tan
19
47
0
10 Apr 2016
Sparse Modeling for Image and Vision Processing
Julien Mairal
Francis R. Bach
Jean Ponce
VLM
42
488
0
12 Nov 2014
Block stochastic gradient iteration for convex and nonconvex optimization
Yangyang Xu
W. Yin
26
134
0
12 Aug 2014
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning
Julien Mairal
79
317
0
18 Feb 2014
1