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Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization

Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization

7 June 2018
Umut Simsekli
Çağatay Yıldız
T. H. Nguyen
G. Richard
A. Cemgil
ArXiv (abs)PDFHTML

Papers citing "Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization"

14 / 14 papers shown
Title
Local Optimality and Generalization Guarantees for the Langevin
  Algorithm via Empirical Metastability
Local Optimality and Generalization Guarantees for the Langevin Algorithm via Empirical Metastability
Belinda Tzen
Tengyuan Liang
Maxim Raginsky
73
32
0
18 Feb 2018
Momentum and Stochastic Momentum for Stochastic Gradient, Newton,
  Proximal Point and Subspace Descent Methods
Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods
Nicolas Loizou
Peter Richtárik
77
202
0
27 Dec 2017
Stochastic L-BFGS: Improved Convergence Rates and Practical Acceleration
  Strategies
Stochastic L-BFGS: Improved Convergence Rates and Practical Acceleration Strategies
Renbo Zhao
W. Haskell
Vincent Y. F. Tan
51
29
0
01 Apr 2017
Langevin Dynamics with Continuous Tempering for Training Deep Neural
  Networks
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks
Nanyang Ye
Zhanxing Zhu
Rafał K. Mantiuk
78
21
0
13 Mar 2017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a
  nonasymptotic analysis
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis
Maxim Raginsky
Alexander Rakhlin
Matus Telgarsky
84
521
0
13 Feb 2017
Asynchronous Stochastic Gradient MCMC with Elastic Coupling
Asynchronous Stochastic Gradient MCMC with Elastic Coupling
Jost Tobias Springenberg
Aaron Klein
Stefan Falkner
Frank Hutter
BDL
37
1
0
02 Dec 2016
Stochastic Gradient MCMC with Stale Gradients
Stochastic Gradient MCMC with Stale Gradients
Changyou Chen
Nan Ding
Chunyuan Li
Yizhe Zhang
Lawrence Carin
BDL
84
23
0
21 Oct 2016
Asynchronous Stochastic Gradient Descent with Delay Compensation
Asynchronous Stochastic Gradient Descent with Delay Compensation
Shuxin Zheng
Qi Meng
Taifeng Wang
Wei Chen
Nenghai Yu
Zhiming Ma
Tie-Yan Liu
133
315
0
27 Sep 2016
A Multi-Batch L-BFGS Method for Machine Learning
A Multi-Batch L-BFGS Method for Machine Learning
A. Berahas
J. Nocedal
Martin Takáč
ODL
84
112
0
19 May 2016
A Linearly-Convergent Stochastic L-BFGS Algorithm
A Linearly-Convergent Stochastic L-BFGS Algorithm
Philipp Moritz
Robert Nishihara
Michael I. Jordan
ODL
84
235
0
09 Aug 2015
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization
Xiangru Lian
Yijun Huang
Y. Li
Ji Liu
141
499
0
27 Jun 2015
Parallel Stochastic Gradient Markov Chain Monte Carlo for Matrix
  Factorisation Models
Parallel Stochastic Gradient Markov Chain Monte Carlo for Matrix Factorisation Models
Umut Simsekli
Hazal Koptagel
Hakan Güldaş
taylan. cemgil
Figen Oztoprak
Ilker Birbil
82
12
0
03 Jun 2015
A Stochastic Quasi-Newton Method for Large-Scale Optimization
A Stochastic Quasi-Newton Method for Large-Scale Optimization
R. Byrd
Samantha Hansen
J. Nocedal
Y. Singer
ODL
114
473
0
27 Jan 2014
Distributed Delayed Stochastic Optimization
Distributed Delayed Stochastic Optimization
Alekh Agarwal
John C. Duchi
139
627
0
28 Apr 2011
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