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Minibatch and Momentum Model-based Methods for Stochastic Weakly Convex
  Optimization
v1v2 (latest)

Minibatch and Momentum Model-based Methods for Stochastic Weakly Convex Optimization

Neural Information Processing Systems (NeurIPS), 2021
6 June 2021
Qi Deng
Wenzhi Gao
ArXiv (abs)PDFHTMLGithub

Papers citing "Minibatch and Momentum Model-based Methods for Stochastic Weakly Convex Optimization"

10 / 10 papers shown
Adaptive Memory Momentum via a Model-Based Framework for Deep Learning Optimization
Adaptive Memory Momentum via a Model-Based Framework for Deep Learning Optimization
Kristi Topollai
A. Choromańska
ODL
417
1
0
06 Oct 2025
Quantitative Convergence Analysis of Projected Stochastic Gradient Descent for Non-Convex Losses via the Goldstein Subdifferential
Quantitative Convergence Analysis of Projected Stochastic Gradient Descent for Non-Convex Losses via the Goldstein Subdifferential
Yuping Zheng
Andrew G. Lamperski
269
0
0
03 Oct 2025
Stochastic Weakly Convex Optimization Beyond Lipschitz Continuity
Stochastic Weakly Convex Optimization Beyond Lipschitz ContinuityInternational Conference on Machine Learning (ICML), 2024
Wenzhi Gao
Qi Deng
314
6
0
25 Jan 2024
Data-driven Piecewise Affine Decision Rules for Stochastic Programming with Covariate Information
Data-driven Piecewise Affine Decision Rules for Stochastic Programming with Covariate Information
Yiyang Zhang
Junyi Liu
Xiaobo Zhao
589
4
0
26 Apr 2023
A Unified Momentum-based Paradigm of Decentralized SGD for Non-Convex
  Models and Heterogeneous Data
A Unified Momentum-based Paradigm of Decentralized SGD for Non-Convex Models and Heterogeneous Data
Haizhou Du
Chengdong Ni
183
3
0
01 Mar 2023
Oracle Complexity of Single-Loop Switching Subgradient Methods for
  Non-Smooth Weakly Convex Functional Constrained Optimization
Oracle Complexity of Single-Loop Switching Subgradient Methods for Non-Smooth Weakly Convex Functional Constrained OptimizationNeural Information Processing Systems (NeurIPS), 2023
Yan Huang
Qihang Lin
430
16
0
30 Jan 2023
Delayed Stochastic Algorithms for Distributed Weakly Convex Optimization
Delayed Stochastic Algorithms for Distributed Weakly Convex Optimization
W. Gao
Qinhao Deng
374
0
0
30 Jan 2023
Sharper Analysis for Minibatch Stochastic Proximal Point Methods:
  Stability, Smoothness, and Deviation
Sharper Analysis for Minibatch Stochastic Proximal Point Methods: Stability, Smoothness, and DeviationJournal of machine learning research (JMLR), 2023
Xiao-Tong Yuan
P. Li
297
3
0
09 Jan 2023
On Convergence of FedProx: Local Dissimilarity Invariant Bounds,
  Non-smoothness and Beyond
On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and BeyondNeural Information Processing Systems (NeurIPS), 2022
Xiao-Tong Yuan
P. Li
FedML
248
111
0
10 Jun 2022
Convergence and Stability of the Stochastic Proximal Point Algorithm
  with Momentum
Convergence and Stability of the Stochastic Proximal Point Algorithm with MomentumConference on Learning for Dynamics & Control (L4DC), 2021
Junhyung Lyle Kim
Panos Toulis
Anastasios Kyrillidis
611
11
0
11 Nov 2021
1
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