A Multi-Batch L-BFGS Method for Machine Learning

A Multi-Batch L-BFGS Method for Machine Learning

19 May 2016

Papers citing "A Multi-Batch L-BFGS Method for Machine Learning"

19 / 19 papers shown

Title
SAPPHIRE: Preconditioned Stochastic Variance Reduction for Faster Large-Scale Statistical Learning Jingruo Sun Zachary Frangella Madeleine Udell 36 0 0 28 Jan 2025
Knowledge Distillation with Adapted Weight Sirong Wu Xi Luo Junjie Liu Yuhui Deng 43 0 0 06 Jan 2025
Second-order Information Promotes Mini-Batch Robustness in Variance-Reduced Gradients Sachin Garg A. Berahas Michal Dereziñski 46 1 0 23 Apr 2024
Learning with SASQuaTCh: a Novel Variational Quantum Transformer Architecture with Kernel-Based Self-Attention Ethan N. Evans Matthew G. Cook Zachary P. Bradshaw Margarite L. LaBorde 48 5 0 21 Mar 2024
Component-Wise Natural Gradient Descent -- An Efficient Neural Network Optimization Tran van Sang Mhd Irvan R. Yamaguchi Toshiyuki Nakata 15 1 0 11 Oct 2022
SP2: A Second Order Stochastic Polyak Method Shuang Li W. Swartworth Martin Takávc Deanna Needell Robert Mansel Gower 26 13 0 17 Jul 2022
Deep Leakage from Model in Federated Learning Zihao Zhao Mengen Luo Wenbo Ding FedML 26 14 0 10 Jun 2022
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination Masaki Adachi Satoshi Hayakawa Martin Jørgensen Harald Oberhauser Michael A. Osborne 22 20 0 09 Jun 2022
Resource-constrained Federated Edge Learning with Heterogeneous Data: Formulation and Analysis Yi Liu Yuanshao Zhu James J. Q. Yu FedML 27 28 0 14 Oct 2021
Adaptive Sampling Quasi-Newton Methods for Zeroth-Order Stochastic Optimization Raghu Bollapragada Stefan M. Wild 35 11 0 24 Sep 2021
An Adaptive Memory Multi-Batch L-BFGS Algorithm for Neural Network Training Federico Zocco Seán F. McLoone ODL 21 4 0 14 Dec 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 34 0 0 26 Aug 2020
SONIA: A Symmetric Blockwise Truncated Optimization Algorithm Majid Jahani M. Nazari R. Tappenden A. Berahas Martin Takávc ODL 11 10 0 06 Jun 2020
Stochastic Calibration of Radio Interferometers S. Yatawatta 14 6 0 02 Mar 2020
Quasi-Newton Methods for Machine Learning: Forget the Past, Just Sample A. Berahas Majid Jahani Peter Richtárik Martin Takávc 24 40 0 28 Jan 2019
Deep Reinforcement Learning via L-BFGS Optimization Chris Paxton Roummel F. Marcia OffRL 11 0 0 06 Nov 2018
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 22 18 0 26 Oct 2018
On the Acceleration of L-BFGS with Second-Order Information and Stochastic Batches Jie Liu Yu Rong Martin Takáč Junzhou Huang ODL 32 7 0 14 Jul 2018
Optimization Methods for Supervised Machine Learning: From Linear Models to Deep Learning Frank E. Curtis K. Scheinberg 39 45 0 30 Jun 2017