SONIA: A Symmetric Blockwise Truncated Optimization Algorithm

6 June 2020

Papers citing "SONIA: A Symmetric Blockwise Truncated Optimization Algorithm"

25 / 25 papers shown

Title
Scaling Up Quasi-Newton Algorithms: Communication Efficient Distributed SR1 Majid Jahani M. Nazari S. Rusakov A. Berahas Martin Takávc 38 14 0 30 May 2019
Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy Majid Jahani Xi He Chenxin Ma Aryan Mokhtari Dheevatsa Mudigere Alejandro Ribeiro Martin Takáč 47 18 0 26 Oct 2018
Trust-Region Algorithms for Training Responses: Machine Learning Methods Using Indefinite Hessian Approximations Jennifer B. Erway J. Griffin Roummel F. Marcia Riadh Omheni 25 24 0 01 Jul 2018
Adaptive Sampling Strategies for Stochastic Optimization Raghu Bollapragada R. Byrd J. Nocedal 39 116 0 30 Oct 2017
Fast and Safe: Accelerated gradient methods with optimality certificates and underestimate sequences Majid Jahani N. V. C. Gudapati Chenxin Ma R. Tappenden Martin Takáč 29 7 0 10 Oct 2017
Second-Order Optimization for Non-Convex Machine Learning: An Empirical Study Peng Xu Farbod Roosta-Khorasani Michael W. Mahoney ODL 50 143 0 25 Aug 2017
A Robust Multi-Batch L-BFGS Method for Machine Learning A. Berahas Martin Takáč AAML ODL 81 44 0 26 Jul 2017
An Investigation of Newton-Sketch and Subsampled Newton Methods A. Berahas Raghu Bollapragada J. Nocedal 44 111 0 17 May 2017
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient Lam M. Nguyen Jie Liu K. Scheinberg Martin Takáč ODL 146 601 0 01 Mar 2017
Exact and Inexact Subsampled Newton Methods for Optimization Raghu Bollapragada R. Byrd J. Nocedal 49 178 0 27 Sep 2016
Optimization Methods for Large-Scale Machine Learning Léon Bottou Frank E. Curtis J. Nocedal 173 3,198 0 15 Jun 2016
Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy Aryan Mokhtari Alejandro Ribeiro ODL 34 32 0 24 May 2016
A Multi-Batch L-BFGS Method for Machine Learning A. Berahas J. Nocedal Martin Takáč ODL 52 110 0 19 May 2016
Stochastic Variance Reduction for Nonconvex Optimization Sashank J. Reddi Ahmed S. Hefny S. Sra Barnabás Póczós Alex Smola 80 598 0 19 Mar 2016
Stop Wasting My Gradients: Practical SVRG Reza Babanezhad Mohamed Osama Ahmed Alim Virani Mark Schmidt Jakub Konecný Scott Sallinen 50 134 0 05 Nov 2015
adaQN: An Adaptive Quasi-Newton Algorithm for Training RNNs N. Keskar A. Berahas ODL 35 35 0 04 Nov 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 813 149,474 0 22 Dec 2014
Global Convergence of Online Limited Memory BFGS Aryan Mokhtari Alejandro Ribeiro 56 164 0 06 Sep 2014
A Stochastic Quasi-Newton Method for Large-Scale Optimization R. Byrd Samantha Hansen J. Nocedal Y. Singer ODL 76 471 0 27 Jan 2014
Minimizing Finite Sums with the Stochastic Average Gradient Mark Schmidt Nicolas Le Roux Francis R. Bach 245 1,246 0 10 Sep 2013
Inexact Coordinate Descent: Complexity and Preconditioning R. Tappenden Peter Richtárik J. Gondzio 55 100 0 19 Apr 2013
Parallel Coordinate Descent Methods for Big Data Optimization Peter Richtárik Martin Takáč 85 487 0 04 Dec 2012
Iteration Complexity of Randomized Block-Coordinate Descent Methods for Minimizing a Composite Function Peter Richtárik Martin Takáč 78 769 0 14 Jul 2011
HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent Feng Niu Benjamin Recht Christopher Ré Stephen J. Wright 137 2,272 0 28 Jun 2011
Hybrid Deterministic-Stochastic Methods for Data Fitting M. Friedlander Mark Schmidt 129 387 0 13 Apr 2011