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Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization
SIAM Journal on Optimization (SIAM J. Optim.), 2016
5 July 2016
Tianlin Li
Shiqian Ma
Shiqian Ma
Wen Liu
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Papers citing
"Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization"
50 / 67 papers shown
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Incremental Quasi-Newton Methods with Faster Superlinear Convergence Rates
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Provably Convergent Plug-and-Play Quasi-Newton Methods
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09 Mar 2023
Stochastic Approximation Beyond Gradient for Signal Processing and Machine Learning
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252
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22 Feb 2023
FOSI: Hybrid First and Second Order Optimization
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Hadar Sivan
Moshe Gabel
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16 Feb 2023
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods
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FedSSO: A Federated Server-Side Second-Order Optimization Algorithm
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20 Jun 2022
Stochastic Variance-Reduced Newton: Accelerating Finite-Sum Minimization with Large Batches
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Can We Do Better Than Random Start? The Power of Data Outsourcing
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A Novel Fast Exact Subproblem Solver for Stochastic Quasi-Newton Cubic Regularized Optimization
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J. Griffin
Wenwen Zhou
S. Yektamaram
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193
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19 Apr 2022
Variance-Reduced Stochastic Quasi-Newton Methods for Decentralized Learning: Part I
IEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2022
Jiaojiao Zhang
Huikang Liu
Anthony Man-Cho So
Qing Ling
236
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19 Jan 2022
Local Quadratic Convergence of Stochastic Gradient Descent with Adaptive Step Size
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Adaptive First- and Second-Order Algorithms for Large-Scale Machine Learning
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Tiphaine Bonniot de Ruisselet
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Andrea Lodi
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Bolstering Stochastic Gradient Descent with Model Building
TOP - An Official Journal of the Spanish Society of Statistics and Operations Research (TOP), 2021
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Özgür Martin
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Figen Oztoprak
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A theoretical and empirical study of new adaptive algorithms with additional momentum steps and shifted updates for stochastic non-convex optimization
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Stochastic Anderson Mixing for Nonconvex Stochastic Optimization
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Laurence Yang
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SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients
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Tensor Normal Training for Deep Learning Models
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Yi Ren
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317
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05 Jun 2021
Differentially private inference via noisy optimization
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Casey Bradshaw
Po-Ling Loh
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19 Mar 2021
Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating
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Qingsong Zhang
Bin Gu
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01 Mar 2021
Kronecker-factored Quasi-Newton Methods for Deep Learning
Yi Ren
Achraf Bahamou
Shiqian Ma
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221
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An Adaptive Stochastic Sequential Quadratic Programming with Differentiable Exact Augmented Lagrangians
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Sen Na
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10 Feb 2021
Stochastic Damped L-BFGS with Controlled Norm of the Hessian Approximation
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Tiphaine Bonniot de Ruisselet
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Asynchronous Parallel Stochastic Quasi-Newton Methods
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Qianqian Tong
Guannan Liang
Xingyu Cai
Chunjiang Zhu
J. Bi
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186
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02 Nov 2020
An adaptive Hessian approximated stochastic gradient MCMC method
Journal of Computational Physics (JCP), 2020
Yating Wang
Wei Deng
Guang Lin
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112
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Variance-Reduced Methods for Machine Learning
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Robert Mansel Gower
Mark Schmidt
Francis R. Bach
Peter Richtárik
265
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02 Oct 2020
Apollo: An Adaptive Parameter-wise Diagonal Quasi-Newton Method for Nonconvex Stochastic Optimization
Xuezhe Ma
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443
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Learning explanations that are hard to vary
International Conference on Learning Representations (ICLR), 2020
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Alexander Neitz
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Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters
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Enhance Curvature Information by Structured Stochastic Quasi-Newton Methods
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153
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Practical Quasi-Newton Methods for Training Deep Neural Networks
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Sketchy Empirical Natural Gradient Methods for Deep Learning
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Dong Xu
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Mengyun Chen
Pengxiang Xu
216
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Structure preserving deep learning
E. Celledoni
Matthias Joachim Ehrhardt
Christian Etmann
R. McLachlan
B. Owren
Carola-Bibiane Schönlieb
Ferdia Sherry
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216
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05 Jun 2020
Fast Stochastic Ordinal Embedding with Variance Reduction and Adaptive Step Size
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019
Ke Ma
Jinshan Zeng
Qianqian Xu
Xiaochun Cao
Wei Liu
Xingtai Lv
168
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01 Dec 2019
A Stochastic Extra-Step Quasi-Newton Method for Nonsmooth Nonconvex Optimization
Mathematical programming (Math. Program.), 2019
Minghan Yang
Andre Milzarek
Zaiwen Wen
Tong Zhang
ODL
180
36
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21 Oct 2019
A Stochastic Variance Reduced Nesterov's Accelerated Quasi-Newton Method
International Conference on Machine Learning and Applications (ICMLA), 2019
Sota Yasuda
Shahrzad Mahboubi
S. Indrapriyadarsini
H. Ninomiya
H. Asai
ODL
54
7
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A Stochastic Quasi-Newton Method with Nesterov's Accelerated Gradient
S. Indrapriyadarsini
Shahrzad Mahboubi
H. Ninomiya
H. Asai
ODL
98
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Combining Stochastic Adaptive Cubic Regularization with Negative Curvature for Nonconvex Optimization
Journal of Optimization Theory and Applications (JOTA), 2019
Seonho Park
Seung Hyun Jung
P. Pardalos
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143
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Chao Du
Kun Xu
Max Welling
Jun Zhu
Bo Zhang
163
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24 Jan 2019
A fast quasi-Newton-type method for large-scale stochastic optimisation
A. Wills
Carl Jidling
Thomas B. Schon
ODL
124
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29 Sep 2018
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