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. 1905.10018
  4. Cited By
Momentum-Based Variance Reduction in Non-Convex SGD

Momentum-Based Variance Reduction in Non-Convex SGD

24 May 2019
Ashok Cutkosky
Francesco Orabona
    ODL
ArXivPDFHTML

Papers citing "Momentum-Based Variance Reduction in Non-Convex SGD"

50 / 77 papers shown
Title
Efficient Curvature-Aware Hypergradient Approximation for Bilevel Optimization
Efficient Curvature-Aware Hypergradient Approximation for Bilevel Optimization
Youran Dong
Junfeng Yang
Wei-Ting Yao
Jin Zhang
130
0
0
04 May 2025
Variance Reduction Methods Do Not Need to Compute Full Gradients: Improved Efficiency through Shuffling
Variance Reduction Methods Do Not Need to Compute Full Gradients: Improved Efficiency through Shuffling
Daniil Medyakov
Gleb Molodtsov
S. Chezhegov
Alexey Rebrikov
Aleksandr Beznosikov
103
0
0
21 Feb 2025
FedTLU: Federated Learning with Targeted Layer Updates
FedTLU: Federated Learning with Targeted Layer Updates
Jong-Ik Park
Carlee Joe-Wong
FedML
84
0
0
28 Jan 2025
Weight for Robustness: A Comprehensive Approach towards Optimal Fault-Tolerant Asynchronous ML
Weight for Robustness: A Comprehensive Approach towards Optimal Fault-Tolerant Asynchronous ML
T. Dahan
Kfir Y. Levy
65
0
0
17 Jan 2025
On the Performance Analysis of Momentum Method: A Frequency Domain Perspective
On the Performance Analysis of Momentum Method: A Frequency Domain Perspective
Xianliang Li
Jun Luo
Zhiwei Zheng
Hanxiao Wang
Li Luo
Lingkun Wen
Linlong Wu
Sheng Xu
72
0
0
29 Nov 2024
Extended convexity and smoothness and their applications in deep learning
Extended convexity and smoothness and their applications in deep learning
Binchuan Qi
Wei Gong
Li Li
61
0
0
08 Oct 2024
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction
Xinwei Zhang
Zhiqi Bu
Borja Balle
Mingyi Hong
Meisam Razaviyayn
Vahab Mirrokni
76
2
0
04 Oct 2024
An Accelerated Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
An Accelerated Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
Xiaochuan Gong
Jie Hao
Mingrui Liu
43
2
0
28 Sep 2024
On the Implicit Relation Between Low-Rank Adaptation and Differential Privacy
On the Implicit Relation Between Low-Rank Adaptation and Differential Privacy
Saber Malekmohammadi
G. Farnadi
24
2
0
26 Sep 2024
Gradient-Free Method for Heavily Constrained Nonconvex Optimization
Gradient-Free Method for Heavily Constrained Nonconvex Optimization
Wanli Shi
Hongchang Gao
Bin Gu
16
5
0
31 Aug 2024
SOREL: A Stochastic Algorithm for Spectral Risks Minimization
SOREL: A Stochastic Algorithm for Spectral Risks Minimization
Yuze Ge
Rujun Jiang
38
0
0
19 Jul 2024
Private Zeroth-Order Nonsmooth Nonconvex Optimization
Private Zeroth-Order Nonsmooth Nonconvex Optimization
Qinzi Zhang
Hoang Tran
Ashok Cutkosky
40
4
0
27 Jun 2024
Accelerated Stochastic Min-Max Optimization Based on Bias-corrected Momentum
Accelerated Stochastic Min-Max Optimization Based on Bias-corrected Momentum
H. Cai
Sulaiman A. Alghunaim
Ali H.Sayed
43
1
0
18 Jun 2024
Random Scaling and Momentum for Non-smooth Non-convex Optimization
Random Scaling and Momentum for Non-smooth Non-convex Optimization
Qinzi Zhang
Ashok Cutkosky
37
4
0
16 May 2024
Robust Decentralized Learning with Local Updates and Gradient Tracking
Robust Decentralized Learning with Local Updates and Gradient Tracking
Sajjad Ghiasvand
Amirhossein Reisizadeh
Mahnoosh Alizadeh
Ramtin Pedarsani
39
3
0
02 May 2024
Order-Optimal Regret with Novel Policy Gradient Approaches in Infinite-Horizon Average Reward MDPs
Order-Optimal Regret with Novel Policy Gradient Approaches in Infinite-Horizon Average Reward MDPs
Swetha Ganesh
Washim Uddin Mondal
Vaneet Aggarwal
44
3
0
02 Apr 2024
Global Convergence Guarantees for Federated Policy Gradient Methods with
  Adversaries
Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries
Swetha Ganesh
Jiayu Chen
Gugan Thoppe
Vaneet Aggarwal
FedML
64
1
0
15 Mar 2024
Non-Convex Stochastic Composite Optimization with Polyak Momentum
Non-Convex Stochastic Composite Optimization with Polyak Momentum
Yuan Gao
Anton Rodomanov
Sebastian U. Stich
31
6
0
05 Mar 2024
Flora: Low-Rank Adapters Are Secretly Gradient Compressors
Flora: Low-Rank Adapters Are Secretly Gradient Compressors
Yongchang Hao
Yanshuai Cao
Lili Mou
16
39
0
05 Feb 2024
Bilevel Optimization under Unbounded Smoothness: A New Algorithm and
  Convergence Analysis
Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis
Jie Hao
Xiaochuan Gong
Mingrui Liu
30
7
0
17 Jan 2024
FedDRO: Federated Compositional Optimization for Distributionally Robust
  Learning
FedDRO: Federated Compositional Optimization for Distributionally Robust Learning
Prashant Khanduri
Chengyin Li
Rafi Ibn Sultan
Yao Qiang
Joerg Kliewer
Dongxiao Zhu
36
0
0
21 Nov 2023
A Coefficient Makes SVRG Effective
A Coefficient Makes SVRG Effective
Yida Yin
Zhiqiu Xu
Zhiyuan Li
Trevor Darrell
Zhuang Liu
33
1
0
09 Nov 2023
Convergence of Sign-based Random Reshuffling Algorithms for Nonconvex
  Optimization
Convergence of Sign-based Random Reshuffling Algorithms for Nonconvex Optimization
Zhen Qin
Zhishuai Liu
Pan Xu
20
1
0
24 Oct 2023
Communication Compression for Byzantine Robust Learning: New Efficient
  Algorithms and Improved Rates
Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates
Ahmad Rammal
Kaja Gruntkowska
Nikita Fedin
Eduard A. Gorbunov
Peter Richtárik
45
5
0
15 Oct 2023
Variance-reduced accelerated methods for decentralized stochastic
  double-regularized nonconvex strongly-concave minimax problems
Variance-reduced accelerated methods for decentralized stochastic double-regularized nonconvex strongly-concave minimax problems
Gabriel Mancino-Ball
Yangyang Xu
20
8
0
14 Jul 2023
Weighted Averaged Stochastic Gradient Descent: Asymptotic Normality and Optimality
Weighted Averaged Stochastic Gradient Descent: Asymptotic Normality and Optimality
Ziyang Wei
Wanrong Zhu
Wei Biao Wu
27
3
0
13 Jul 2023
Federated Multi-Sequence Stochastic Approximation with Local
  Hypergradient Estimation
Federated Multi-Sequence Stochastic Approximation with Local Hypergradient Estimation
Davoud Ataee Tarzanagh
Mingchen Li
Pranay Sharma
Samet Oymak
24
0
0
02 Jun 2023
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates
  and Practical Features
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
On Momentum-Based Gradient Methods for Bilevel Optimization with
  Nonconvex Lower-Level
On Momentum-Based Gradient Methods for Bilevel Optimization with Nonconvex Lower-Level
Feihu Huang
27
18
0
07 Mar 2023
Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization
Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization
Feihu Huang
Chunyu Xuan
Xinrui Wang
Siqi Zhang
Songcan Chen
28
7
0
07 Mar 2023
A One-Sample Decentralized Proximal Algorithm for Non-Convex Stochastic
  Composite Optimization
A One-Sample Decentralized Proximal Algorithm for Non-Convex Stochastic Composite Optimization
Tesi Xiao
Xuxing Chen
Krishnakumar Balasubramanian
Saeed Ghadimi
36
10
0
20 Feb 2023
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order
  Stationary Points and Excess Risks
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks
Arun Ganesh
Daogao Liu
Sewoong Oh
Abhradeep Thakurta
ODL
27
12
0
20 Feb 2023
Breaking the Lower Bound with (Little) Structure: Acceleration in
  Non-Convex Stochastic Optimization with Heavy-Tailed Noise
Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise
Zijian Liu
Jiawei Zhang
Zhengyuan Zhou
32
12
0
14 Feb 2023
Near-Optimal Non-Convex Stochastic Optimization under Generalized
  Smoothness
Near-Optimal Non-Convex Stochastic Optimization under Generalized Smoothness
Zijian Liu
Srikanth Jagabathula
Zhengyuan Zhou
16
4
0
13 Feb 2023
Stochastic Dimension-reduced Second-order Methods for Policy
  Optimization
Stochastic Dimension-reduced Second-order Methods for Policy Optimization
Jinsong Liu
Chen Xie
Qinwen Deng
Dongdong Ge
Yi-Li Ye
24
1
0
28 Jan 2023
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic
  Optimization
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization
Le‐Yu Chen
Jing Xu
Luo Luo
31
15
0
16 Jan 2023
Balance is Essence: Accelerating Sparse Training via Adaptive Gradient
  Correction
Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction
Bowen Lei
Dongkuan Xu
Ruqi Zhang
Shuren He
Bani Mallick
29
6
0
09 Jan 2023
Stochastic Inexact Augmented Lagrangian Method for Nonconvex Expectation
  Constrained Optimization
Stochastic Inexact Augmented Lagrangian Method for Nonconvex Expectation Constrained Optimization
Zichong Li
Pinzhuo Chen
Sijia Liu
Songtao Lu
Yangyang Xu
27
17
0
19 Dec 2022
Gradient Descent-Type Methods: Background and Simple Unified Convergence
  Analysis
Gradient Descent-Type Methods: Background and Simple Unified Convergence Analysis
Quoc Tran-Dinh
Marten van Dijk
34
0
0
19 Dec 2022
Variance-Reduced Conservative Policy Iteration
Variance-Reduced Conservative Policy Iteration
Naman Agarwal
Brian Bullins
Karan Singh
24
3
0
12 Dec 2022
Decentralized Stochastic Gradient Descent Ascent for Finite-Sum Minimax
  Problems
Decentralized Stochastic Gradient Descent Ascent for Finite-Sum Minimax Problems
Hongchang Gao
24
16
0
06 Dec 2022
An Efficient Stochastic Algorithm for Decentralized
  Nonconvex-Strongly-Concave Minimax Optimization
An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization
Le‐Yu Chen
Haishan Ye
Luo Luo
65
5
0
05 Dec 2022
Adaptive Stochastic Optimisation of Nonconvex Composite Objectives
Adaptive Stochastic Optimisation of Nonconvex Composite Objectives
Weijia Shao
F. Sivrikaya
S. Albayrak
13
0
0
21 Nov 2022
Fast Adaptive Federated Bilevel Optimization
Fast Adaptive Federated Bilevel Optimization
Feihu Huang
FedML
20
7
0
02 Nov 2022
Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader
  Models
Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader Models
Shujian Zhang
Chengyue Gong
Xingchao Liu
RALM
43
6
0
02 Nov 2022
Momentum Aggregation for Private Non-convex ERM
Momentum Aggregation for Private Non-convex ERM
Hoang Tran
Ashok Cutkosky
26
14
0
12 Oct 2022
SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum
  Cocoercive Variational Inequalities
SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities
Aleksandr Beznosikov
Alexander Gasnikov
34
2
0
12 Oct 2022
SENDER: SEmi-Nonlinear Deep Efficient Reconstructor for Extraction
  Canonical, Meta, and Sub Functional Connectivity in the Human Brain
SENDER: SEmi-Nonlinear Deep Efficient Reconstructor for Extraction Canonical, Meta, and Sub Functional Connectivity in the Human Brain
Wei Zhang
Yun-Jian Bao
9
0
0
12 Sep 2022
Multi-block-Single-probe Variance Reduced Estimator for Coupled
  Compositional Optimization
Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization
Wei Jiang
Gang Li
Yibo Wang
Lijun Zhang
Tianbao Yang
32
16
0
18 Jul 2022
Multi-block Min-max Bilevel Optimization with Applications in Multi-task
  Deep AUC Maximization
Multi-block Min-max Bilevel Optimization with Applications in Multi-task Deep AUC Maximization
Quanqi Hu
Yongjian Zhong
Tianbao Yang
25
16
0
01 Jun 2022
12
Next