ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1306.4650
  4. Cited By
Stochastic Majorization-Minimization Algorithms for Large-Scale
  Optimization

Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization

19 June 2013
Julien Mairal
ArXivPDFHTML

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

22 / 22 papers shown
Title
Online Learning Under A Separable Stochastic Approximation Framework
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning
Julien Mairal
79
317
0
18 Feb 2014
1