Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning

18 February 2014

Papers citing "Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning"

50 / 113 papers shown

Title
It's All Connected: A Journey Through Test-Time Memorization, Attentional Bias, Retention, and Online Optimization Ali Behrouz Meisam Razaviyayn Peilin Zhong Vahab Mirrokni 38 0 0 17 Apr 2025
Efficient and Distributed Large-Scale Point Cloud Bundle Adjustment via Majorization-Minimization Rundong Li Zheng Liu Hairuo Wei Yixi Cai H. Li Fu Zhang 47 0 0 26 Feb 2025
SPAM: Stochastic Proximal Point Method with Momentum Variance Reduction for Non-convex Cross-Device Federated Learning Avetik G. Karagulyan Egor Shulgin Abdurakhmon Sadiev Peter Richtárik FedML 46 2 0 30 May 2024
Efficient algorithms for regularized Poisson Non-negative Matrix Factorization Nathanael Perraudin Adrien Teutrie Cécile Hébert G. Obozinski 27 1 0 25 Apr 2024
Stochastic optimization with arbitrary recurrent data sampling William G. Powell Hanbaek Lyu 29 0 0 15 Jan 2024
A Coefficient Makes SVRG Effective Yida Yin Zhiqiu Xu Zhiyuan Li Trevor Darrell Zhuang Liu 25 1 0 09 Nov 2023
$Computing Approximate $\ell_p$ Sensitivities$ Computing Approximate $\ell_p$ Sensitivities Swati Padmanabhan David P. Woodruff Qiuyi Zhang 45 0 0 07 Nov 2023
Faster Stochastic Algorithms for Minimax Optimization under Polyak--Łojasiewicz Conditions Le‐Yu Chen Boyuan Yao Luo Luo 14 15 0 29 Jul 2023
On the Importance of Feature Decorrelation for Unsupervised Representation Learning in Reinforcement Learning Hojoon Lee Ko-tik Lee Dongyoon Hwang Hyunho Lee ByungKun Lee Jaegul Choo SSL OOD 20 5 0 09 Jun 2023
Block Coordinate Plug-and-Play Methods for Blind Inverse Problems Weijie Gan S. Shoushtari Yuyang Hu Jiaming Liu Hongyu An Ulugbek S. Kamilov 20 11 0 22 May 2023
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features Aleksandr Beznosikov David Dobre Gauthier Gidel 25 5 0 23 Apr 2023
Accelerated Distributed Aggregative Optimization Jiaxu Liu Song Chen Shengze Cai Chaoyang Xu 22 6 0 17 Apr 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
Target-based Surrogates for Stochastic Optimization J. Lavington Sharan Vaswani Reza Babanezhad Mark W. Schmidt Nicolas Le Roux 46 5 0 06 Feb 2023
Stochastic Optimization for Spectral Risk Measures Ronak R. Mehta Vincent Roulet Krishna Pillutla Lang Liu Zaïd Harchaoui 32 6 0 10 Dec 2022
Reconstruction of gene regulatory network via sparse optimization Jiashu Lou Leyi Cui Wenxuan Qiu 22 0 0 11 Nov 2022
Convex Clustering through MM: An Efficient Algorithm to Perform Hierarchical Clustering Daniel J. W. Touw P. Groenen Y. Terada 12 3 0 03 Nov 2022
The Stochastic Proximal Distance Algorithm Hao Jiang Jason Xu 25 0 0 21 Oct 2022
Joint control variate for faster black-box variational inference Xi Wang Tomas Geffner Justin Domke BDL DRL 11 0 0 13 Oct 2022
SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities Aleksandr Beznosikov Alexander Gasnikov 25 2 0 12 Oct 2022
Light-weight probing of unsupervised representations for Reinforcement Learning Wancong Zhang Anthony GX-Chen Vlad Sobal Yann LeCun Nicolas Carion SSL OffRL 35 13 0 25 Aug 2022
Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity Sally Dong Haotian Jiang Y. Lee Swati Padmanabhan Guanghao Ye 20 2 0 07 Aug 2022
Online Inference for Mixture Model of Streaming Graph Signals with Non-White Excitation Yiran He Hoi-To Wai 23 2 0 28 Jul 2022
SPIRAL: A superlinearly convergent incremental proximal algorithm for nonconvex finite sum minimization Pourya Behmandpoor P. Latafat Andreas Themelis Marc Moonen Panagiotis Patrinos 24 2 0 17 Jul 2022
On a class of geodesically convex optimization problems solved via Euclidean MM methods Melanie Weber S. Sra 9 4 0 22 Jun 2022
Bregman Power k-Means for Clustering Exponential Family Data Adithya Vellal Saptarshi Chakraborty Jason Xu 22 6 0 22 Jun 2022
Convergence of online $k$ -means S. Dasgupta G. Mahajan Geelon So 13 3 0 22 Feb 2022
Random-reshuffled SARAH does not need a full gradient computations Aleksandr Beznosikov Martin Takáč 13 7 0 26 Nov 2021
L-DQN: An Asynchronous Limited-Memory Distributed Quasi-Newton Method Bugra Can Saeed Soori M. Dehnavi Mert Gurbuzbalaban 32 1 0 20 Aug 2021
Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders Xinmeng Huang Kun Yuan Xianghui Mao W. Yin 17 12 0 25 Apr 2021
Adversarially-Trained Nonnegative Matrix Factorization Ting Cai Vincent Y. F. Tan Cédric Févotte 11 6 0 10 Apr 2021
ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method Zhize Li 30 14 0 21 Mar 2021
Recent Theoretical Advances in Non-Convex Optimization Marina Danilova Pavel Dvurechensky Alexander Gasnikov Eduard A. Gorbunov Sergey Guminov Dmitry Kamzolov Innokentiy Shibaev 20 76 0 11 Dec 2020
Kernel k-Means, By All Means: Algorithms and Strong Consistency Debolina Paul Saptarshi Chakraborty Swagatam Das Jason Xu 13 7 0 12 Nov 2020
SGB: Stochastic Gradient Bound Method for Optimizing Partition Functions Junchang Wang A. Choromańska 21 0 0 03 Nov 2020
Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent Frederik Kunstner Raunak Kumar Mark W. Schmidt 27 21 0 02 Nov 2020
Variance-Reduced Methods for Machine Learning Robert Mansel Gower Mark W. Schmidt Francis R. Bach Peter Richtárik 19 110 0 02 Oct 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 19 0 0 26 Aug 2020
NoPeek: Information leakage reduction to share activations in distributed deep learning Praneeth Vepakomma Abhishek Singh O. Gupta Ramesh Raskar MIACV FedML 16 84 0 20 Aug 2020
Online Robust and Adaptive Learning from Data Streams Shintaro Fukushima Atsushi Nitanda Kenji Yamanishi 19 3 0 23 Jul 2020
Globally-convergent Iteratively Reweighted Least Squares for Robust Regression Problems B. Mukhoty G. Gopakumar Prateek Jain Purushottam Kar 22 30 0 25 Jun 2020
Advances in Asynchronous Parallel and Distributed Optimization By Mahmoud Assran Arda Aytekin Hamid Reza Feyzmahdavian M. Johansson Michael G. Rabbat 12 77 0 24 Jun 2020
Truncated Inference for Latent Variable Optimization Problems: Application to Robust Estimation and Learning Christopher Zach Huu Le 17 4 0 12 Mar 2020
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems Filip Hanzely D. Kovalev Peter Richtárik 29 17 0 11 Feb 2020
On the Complexity of Minimizing Convex Finite Sums Without Using the Indices of the Individual Functions Yossi Arjevani Amit Daniely Stefanie Jegelka Hongzhou Lin 13 2 0 09 Feb 2020
Entropy Regularized Power k-Means Clustering Saptarshi Chakraborty Debolina Paul Swagatam Das Jason Xu 15 2 0 10 Jan 2020
Robust Aggregation for Federated Learning Krishna Pillutla Sham Kakade Zaïd Harchaoui FedML 30 629 0 31 Dec 2019
Cyanure: An Open-Source Toolbox for Empirical Risk Minimization for Python, C++, and soon more Julien Mairal 19 22 0 17 Dec 2019
Majorization Minimization Technique for Optimally Solving Deep Dictionary Learning Vanika Singhal A. Majumdar 15 17 0 11 Dec 2019
Stochastic DCA for minimizing a large sum of DC functions with application to Multi-class Logistic Regression Hoai An Le Thi L. Minh Phan Duy Nhat Bach Tran 22 24 0 10 Nov 2019