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SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path
  Integrated Differential Estimator

SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator

4 July 2018
Cong Fang
C. J. Li
Zhouchen Lin
Tong Zhang
ArXivPDFHTML

Papers citing "SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator"

50 / 109 papers shown
Title
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
A single-loop SPIDER-type stochastic subgradient method for expectation-constrained nonconvex nonsmooth optimization
A single-loop SPIDER-type stochastic subgradient method for expectation-constrained nonconvex nonsmooth optimization
Wei Liu
Yangyang Xu
71
3
0
31 Jan 2025
Adaptive Batch Size for Privately Finding Second-Order Stationary Points
Adaptive Batch Size for Privately Finding Second-Order Stationary Points
Daogao Liu
Kunal Talwar
156
0
0
10 Oct 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
63
0
0
08 Oct 2024
Obtaining Lower Query Complexities through Lightweight Zeroth-Order
  Proximal Gradient Algorithms
Obtaining Lower Query Complexities through Lightweight Zeroth-Order Proximal Gradient Algorithms
Bin Gu
Xiyuan Wei
Hualin Zhang
Yi Chang
Heng-Chiao Huang
FedML
23
0
0
03 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
50
2
0
28 Sep 2024
Gradient-Free Method for Heavily Constrained Nonconvex Optimization
Gradient-Free Method for Heavily Constrained Nonconvex Optimization
Wanli Shi
Hongchang Gao
Bin Gu
21
5
0
31 Aug 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
Comparisons Are All You Need for Optimizing Smooth Functions
Comparisons Are All You Need for Optimizing Smooth Functions
Chenyi Zhang
Tongyang Li
AAML
37
1
0
19 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
42
3
0
02 May 2024
Stochastic Halpern iteration in normed spaces and applications to reinforcement learning
Stochastic Halpern iteration in normed spaces and applications to reinforcement learning
Mario Bravo
Juan Pablo Contreras
45
3
0
19 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
37
6
0
05 Mar 2024
Probabilistic Guarantees of Stochastic Recursive Gradient in Non-Convex
  Finite Sum Problems
Probabilistic Guarantees of Stochastic Recursive Gradient in Non-Convex Finite Sum Problems
Yanjie Zhong
Jiaqi Li
Soumendra Lahiri
27
1
0
29 Jan 2024
On the Stochastic (Variance-Reduced) Proximal Gradient Method for
  Regularized Expected Reward Optimization
On the Stochastic (Variance-Reduced) Proximal Gradient Method for Regularized Expected Reward Optimization
Ling Liang
Haizhao Yang
14
1
0
23 Jan 2024
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
Adaptive Mirror Descent Bilevel Optimization
Adaptive Mirror Descent Bilevel Optimization
Feihu Huang
40
1
0
08 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
23
1
0
24 Oct 2023
Decentralized Gradient-Free Methods for Stochastic Non-Smooth Non-Convex
  Optimization
Decentralized Gradient-Free Methods for Stochastic Non-Smooth Non-Convex Optimization
Zhenwei Lin
Jingfan Xia
Qi Deng
Luo Luo
31
3
0
18 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
On the Parallel Complexity of Multilevel Monte Carlo in Stochastic
  Gradient Descent
On the Parallel Complexity of Multilevel Monte Carlo in Stochastic Gradient Descent
Kei Ishikawa
BDL
63
0
0
03 Oct 2023
Oracle Complexity Reduction for Model-free LQR: A Stochastic
  Variance-Reduced Policy Gradient Approach
Oracle Complexity Reduction for Model-free LQR: A Stochastic Variance-Reduced Policy Gradient Approach
Leonardo F. Toso
Han Wang
James Anderson
37
2
0
19 Sep 2023
Achieving Linear Speedup in Decentralized Stochastic Compositional
  Minimax Optimization
Achieving Linear Speedup in Decentralized Stochastic Compositional Minimax Optimization
Hongchang Gao
40
1
0
25 Jul 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
Efficient preconditioned stochastic gradient descent for estimation in
  latent variable models
Efficient preconditioned stochastic gradient descent for estimation in latent variable models
C. Baey
Maud Delattre
E. Kuhn
Jean-Benoist Léger
Sarah Lemler
21
4
0
22 Jun 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
26
0
0
02 Jun 2023
How to escape sharp minima with random perturbations
How to escape sharp minima with random perturbations
Kwangjun Ahn
Ali Jadbabaie
S. Sra
ODL
34
6
0
25 May 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
32
18
0
07 Mar 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
Solving stochastic weak Minty variational inequalities without
  increasing batch size
Solving stochastic weak Minty variational inequalities without increasing batch size
Thomas Pethick
Olivier Fercoq
P. Latafat
Panagiotis Patrinos
V. Cevher
21
23
0
17 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
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
29
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
35
6
0
09 Jan 2023
Stochastic Variable Metric Proximal Gradient with variance reduction for
  non-convex composite optimization
Stochastic Variable Metric Proximal Gradient with variance reduction for non-convex composite optimization
G. Fort
Eric Moulines
46
6
0
02 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
32
17
0
19 Dec 2022
Variance-Reduced Conservative Policy Iteration
Variance-Reduced Conservative Policy Iteration
Naman Agarwal
Brian Bullins
Karan Singh
32
3
0
12 Dec 2022
Cyclic Block Coordinate Descent With Variance Reduction for Composite
  Nonconvex Optimization
Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization
Xu Cai
Chaobing Song
Stephen J. Wright
Jelena Diakonikolas
33
14
0
09 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
Zeroth-Order Alternating Gradient Descent Ascent Algorithms for a Class
  of Nonconvex-Nonconcave Minimax Problems
Zeroth-Order Alternating Gradient Descent Ascent Algorithms for a Class of Nonconvex-Nonconcave Minimax Problems
Zi Xu
Ziqi Wang
Junlin Wang
Y. Dai
21
11
0
24 Nov 2022
Adaptive Stochastic Optimisation of Nonconvex Composite Objectives
Adaptive Stochastic Optimisation of Nonconvex Composite Objectives
Weijia Shao
F. Sivrikaya
S. Albayrak
21
0
0
21 Nov 2022
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural
  Policy Gradient Methods
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods
Yanli Liu
Kaipeng Zhang
Tamer Basar
W. Yin
45
102
0
15 Nov 2022
Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum
  Minimization
Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization
Ali Kavis
Stratis Skoulakis
Kimon Antonakopoulos
L. Dadi
V. Cevher
24
15
0
03 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
40
2
0
12 Oct 2022
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without
  Gradients
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients
Hualin Zhang
Huan Xiong
Bin Gu
35
7
0
04 Oct 2022
On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling
  Walks
On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks
Yizhou Liu
Weijie J. Su
Tongyang Li
27
18
0
29 Sep 2022
NET-FLEET: Achieving Linear Convergence Speedup for Fully Decentralized
  Federated Learning with Heterogeneous Data
NET-FLEET: Achieving Linear Convergence Speedup for Fully Decentralized Federated Learning with Heterogeneous Data
Xin Zhang
Minghong Fang
Zhuqing Liu
Haibo Yang
Jia-Wei Liu
Zhengyuan Zhu
FedML
25
14
0
17 Aug 2022
SYNTHESIS: A Semi-Asynchronous Path-Integrated Stochastic Gradient
  Method for Distributed Learning in Computing Clusters
SYNTHESIS: A Semi-Asynchronous Path-Integrated Stochastic Gradient Method for Distributed Learning in Computing Clusters
Zhuqing Liu
Xin Zhang
Jia-Wei Liu
38
1
0
17 Aug 2022
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