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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"

28 / 78 papers shown
Title
Proxy Convexity: A Unified Framework for the Analysis of Neural Networks
  Trained by Gradient Descent
Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent
Spencer Frei
Quanquan Gu
15
25
0
25 Jun 2021
Provably Faster Algorithms for Bilevel Optimization
Provably Faster Algorithms for Bilevel Optimization
Junjie Yang
Kaiyi Ji
Yingbin Liang
35
132
0
08 Jun 2021
Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max
  Optimization
Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization
Haochuan Li
Yi Tian
Jingzhao Zhang
Ali Jadbabaie
22
40
0
18 Apr 2021
Greedy-GQ with Variance Reduction: Finite-time Analysis and Improved
  Complexity
Greedy-GQ with Variance Reduction: Finite-time Analysis and Improved Complexity
Shaocong Ma
Ziyi Chen
Yi Zhou
Shaofeng Zou
13
11
0
30 Mar 2021
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization
Siqi Zhang
Junchi Yang
Cristóbal Guzmán
Negar Kiyavash
Niao He
23
60
0
29 Mar 2021
ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method
ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method
Zhize Li
28
14
0
21 Mar 2021
Non-Euclidean Differentially Private Stochastic Convex Optimization:
  Optimal Rates in Linear Time
Non-Euclidean Differentially Private Stochastic Convex Optimization: Optimal Rates in Linear Time
Raef Bassily
Cristóbal Guzmán
Anupama Nandi
52
66
0
01 Mar 2021
MARINA: Faster Non-Convex Distributed Learning with Compression
MARINA: Faster Non-Convex Distributed Learning with Compression
Eduard A. Gorbunov
Konstantin Burlachenko
Zhize Li
Peter Richtárik
22
108
0
15 Feb 2021
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse
  in Imbalanced Training
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training
Cong Fang
Hangfeng He
Qi Long
Weijie J. Su
FAtt
122
165
0
29 Jan 2021
Efficient Semi-Implicit Variational Inference
Efficient Semi-Implicit Variational Inference
Vincent Moens
Hang Ren
A. Maraval
Rasul Tutunov
Jun Wang
H. Ammar
80
6
0
15 Jan 2021
Faster Non-Convex Federated Learning via Global and Local Momentum
Faster Non-Convex Federated Learning via Global and Local Momentum
Rudrajit Das
Anish Acharya
Abolfazl Hashemi
Sujay Sanghavi
Inderjit S. Dhillon
Ufuk Topcu
FedML
24
82
0
07 Dec 2020
A Stochastic Path-Integrated Differential EstimatoR Expectation
  Maximization Algorithm
A Stochastic Path-Integrated Differential EstimatoR Expectation Maximization Algorithm
G. Fort
Eric Moulines
Hoi-To Wai
TPM
14
7
0
30 Nov 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for
  Data and Parameters
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters
Filip Hanzely
19
0
0
26 Aug 2020
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for
  Nonconvex Optimization
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization
Zhize Li
Hongyan Bao
Xiangliang Zhang
Peter Richtárik
ODL
24
125
0
25 Aug 2020
Privacy-Preserving Asynchronous Federated Learning Algorithms for
  Multi-Party Vertically Collaborative Learning
Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning
Bin Gu
An Xu
Zhouyuan Huo
Cheng Deng
Heng-Chiao Huang
FedML
30
27
0
14 Aug 2020
An Online Method for A Class of Distributionally Robust Optimization
  with Non-Convex Objectives
An Online Method for A Class of Distributionally Robust Optimization with Non-Convex Objectives
Qi Qi
Zhishuai Guo
Yi Tian Xu
R. L. Jin
Tianbao Yang
18
44
0
17 Jun 2020
Optimal Complexity in Decentralized Training
Optimal Complexity in Decentralized Training
Yucheng Lu
Christopher De Sa
25
71
0
15 Jun 2020
Biased Stochastic First-Order Methods for Conditional Stochastic
  Optimization and Applications in Meta Learning
Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning
Yifan Hu
Siqi Zhang
Xin Chen
Niao He
ODL
20
54
0
25 Feb 2020
Variance Reduced Coordinate Descent with Acceleration: New Method With a
  Surprising Application to Finite-Sum Problems
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems
Filip Hanzely
D. Kovalev
Peter Richtárik
27
17
0
11 Feb 2020
History-Gradient Aided Batch Size Adaptation for Variance Reduced
  Algorithms
History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms
Kaiyi Ji
Zhe Wang
Bowen Weng
Yi Zhou
Wei Zhang
Yingbin Liang
ODL
13
5
0
21 Oct 2019
Sample Efficient Policy Gradient Methods with Recursive Variance
  Reduction
Sample Efficient Policy Gradient Methods with Recursive Variance Reduction
Pan Xu
F. Gao
Quanquan Gu
23
83
0
18 Sep 2019
Stochastic First-order Methods for Convex and Nonconvex Functional
  Constrained Optimization
Stochastic First-order Methods for Convex and Nonconvex Functional Constrained Optimization
Digvijay Boob
Qi Deng
Guanghui Lan
39
92
0
07 Aug 2019
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization
Rong Ge
Zhize Li
Weiyao Wang
Xiang Wang
17
33
0
01 May 2019
Quantized Frank-Wolfe: Faster Optimization, Lower Communication, and
  Projection Free
Quantized Frank-Wolfe: Faster Optimization, Lower Communication, and Projection Free
Mingrui Zhang
Lin Chen
Aryan Mokhtari
Hamed Hassani
Amin Karbasi
11
8
0
17 Feb 2019
R-SPIDER: A Fast Riemannian Stochastic Optimization Algorithm with
  Curvature Independent Rate
R-SPIDER: A Fast Riemannian Stochastic Optimization Algorithm with Curvature Independent Rate
J. Zhang
Hongyi Zhang
S. Sra
11
39
0
10 Nov 2018
Stochastic Nested Variance Reduction for Nonconvex Optimization
Stochastic Nested Variance Reduction for Nonconvex Optimization
Dongruo Zhou
Pan Xu
Quanquan Gu
19
146
0
20 Jun 2018
AdaGrad stepsizes: Sharp convergence over nonconvex landscapes
AdaGrad stepsizes: Sharp convergence over nonconvex landscapes
Rachel A. Ward
Xiaoxia Wu
Léon Bottou
ODL
17
357
0
05 Jun 2018
Stochastic Variance-Reduced Cubic Regularization for Nonconvex
  Optimization
Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization
Zhe Wang
Yi Zhou
Yingbin Liang
Guanghui Lan
21
46
0
20 Feb 2018
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