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Optimizing Neural Networks with Kronecker-factored Approximate Curvature

19 March 2015

Papers citing "Optimizing Neural Networks with Kronecker-factored Approximate Curvature"

50 / 645 papers shown

Title
Task2Vec: Task Embedding for Meta-Learning Alessandro Achille Michael Lam Rahul Tewari Avinash Ravichandran Subhransu Maji Charless C. Fowlkes Stefano Soatto Pietro Perona SSL 83 317 0 10 Feb 2019
Meta-Curvature Eunbyung Park Junier B. Oliva BDL 89 124 0 09 Feb 2019
Modular Block-diagonal Curvature Approximations for Feedforward Architectures Felix Dangel Stefan Harmeling Philipp Hennig 88 11 0 05 Feb 2019
Riemannian adaptive stochastic gradient algorithms on matrix manifolds Hiroyuki Kasai Pratik Jawanpuria Bamdev Mishra 86 3 0 04 Feb 2019
Predictive Uncertainty Quantification with Compound Density Networks Agustinus Kristiadi Sina Daubener Asja Fischer BDL UQCV 83 17 0 04 Feb 2019
Improving SGD convergence by online linear regression of gradients in multiple statistically relevant directions J. Duda ODL 48 1 0 31 Jan 2019
Discretizing Continuous Action Space for On-Policy Optimization Yunhao Tang Shipra Agrawal OffRL 107 124 0 29 Jan 2019
Large-Batch Training for LSTM and Beyond Yang You Jonathan Hseu Chris Ying J. Demmel Kurt Keutzer Cho-Jui Hsieh 65 91 0 24 Jan 2019
Hamiltonian Monte-Carlo for Orthogonal Matrices V. Yanush D. Kropotov 33 1 0 23 Jan 2019
On-Policy Trust Region Policy Optimisation with Replay Buffers D. Kangin N. Pugeault OffRL 23 3 0 18 Jan 2019
The Extended Kalman Filter is a Natural Gradient Descent in Trajectory Space Yann Ollivier 87 21 0 03 Jan 2019
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning Peter F. Schulam Suchi Saria OOD 101 104 0 02 Jan 2019
KF-LAX: Kronecker-factored curvature estimation for control variate optimization in reinforcement learning Mohammad Firouzi 28 0 0 11 Dec 2018
Natural Option Critic Saket Tiwari Philip S. Thomas 57 22 0 04 Dec 2018
Eigenvalue Corrected Noisy Natural Gradient Juhan Bae Guodong Zhang Roger C. Grosse 100 18 0 30 Nov 2018
Large-Scale Distributed Second-Order Optimization Using Kronecker-Factored Approximate Curvature for Deep Convolutional Neural Networks Kazuki Osawa Yohei Tsuji Yuichiro Ueno Akira Naruse Rio Yokota Satoshi Matsuoka ODL 120 95 0 29 Nov 2018
Deep Frank-Wolfe For Neural Network Optimization Leonard Berrada Andrew Zisserman M. P. Kumar ODL 67 40 0 19 Nov 2018
Natural Environment Benchmarks for Reinforcement Learning Amy Zhang Yuxin Wu Joelle Pineau OffRL OOD 69 69 0 14 Nov 2018
Measuring the Effects of Data Parallelism on Neural Network Training Christopher J. Shallue Jaehoon Lee J. Antognini J. Mamou J. Ketterling Yao Wang 129 409 0 08 Nov 2018
Three Mechanisms of Weight Decay Regularization Guodong Zhang Chaoqi Wang Bowen Xu Roger C. Grosse 75 260 0 29 Oct 2018
Information Geometry of Orthogonal Initializations and Training Piotr A. Sokól Il-Su Park AI4CE 136 17 0 09 Oct 2018
Dynamics and Reachability of Learning Tasks Alessandro Achille G. Mbeng Stefano Soatto 19 7 0 04 Oct 2018
Directional Analysis of Stochastic Gradient Descent via von Mises-Fisher Distributions in Deep learning Cheolhyoung Lee Kyunghyun Cho Wanmo Kang 68 8 0 29 Sep 2018
Boosting Trust Region Policy Optimization by Normalizing Flows Policy Yunhao Tang Shipra Agrawal TPM 110 31 0 27 Sep 2018
Preconditioner on Matrix Lie Group for SGD Xi-Lin Li 51 16 0 26 Sep 2018
A Coordinate-Free Construction of Scalable Natural Gradient Kevin Luk Roger C. Grosse 56 11 0 30 Aug 2018
Multi-Agent Generative Adversarial Imitation Learning Jiaming Song Hongyu Ren Dorsa Sadigh Stefano Ermon GAN 65 224 0 26 Jul 2018
Bayesian filtering unifies adaptive and non-adaptive neural network optimization methods Laurence Aitchison ODL 138 21 0 19 Jul 2018
Convergence guarantees for RMSProp and ADAM in non-convex optimization and an empirical comparison to Nesterov acceleration Soham De Anirbit Mukherjee Enayat Ullah 79 101 0 18 Jul 2018
On the Acceleration of L-BFGS with Second-Order Information and Stochastic Batches Jie Liu Yu Rong Martin Takáč Junzhou Huang ODL 68 7 0 14 Jul 2018
The decoupled extended Kalman filter for dynamic exponential-family factorization models C. Gomez-Uribe Brian Karrer 89 6 0 26 Jun 2018
Stochastic natural gradient descent draws posterior samples in function space Samuel L. Smith Daniel Duckworth Semon Rezchikov Quoc V. Le Jascha Narain Sohl-Dickstein BDL 85 6 0 25 Jun 2018
Fast Approximate Natural Gradient Descent in a Kronecker-factored Eigenbasis Thomas George César Laurent Xavier Bouthillier Nicolas Ballas Pascal Vincent ODL 115 156 0 11 Jun 2018
Bayesian Model-Agnostic Meta-Learning Taesup Kim Jaesik Yoon Ousmane Amadou Dia Sungwoong Kim Yoshua Bengio Sungjin Ahn UQCV BDL 309 504 0 11 Jun 2018
Efficient Full-Matrix Adaptive Regularization Naman Agarwal Brian Bullins Xinyi Chen Elad Hazan Karan Singh Cyril Zhang Yi Zhang 63 21 0 08 Jun 2018
Scalable Natural Gradient Langevin Dynamics in Practice Henri Palacci H. Hess BDL 38 8 0 07 Jun 2018
Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach Ryo Karakida S. Akaho S. Amari FedML 201 146 0 04 Jun 2018
Meta-Learning with Hessian-Free Approach in Deep Neural Nets Training Boyu Chen Wenlian Lu Ernest Fokoue 52 1 0 22 May 2018
Measuring and regularizing networks in function space Ari S. Benjamin David Rolnick Konrad Paul Kording 82 140 0 21 May 2018
Small steps and giant leaps: Minimal Newton solvers for Deep Learning João F. Henriques Sébastien Ehrhardt Samuel Albanie Andrea Vedaldi ODL 57 22 0 21 May 2018
Online Structured Laplace Approximations For Overcoming Catastrophic Forgetting H. Ritter Aleksandar Botev David Barber BDL CLL 106 335 0 20 May 2018
Block Mean Approximation for Efficient Second Order Optimization Yao Lu Mehrtash Harandi Leonid Sigal Razvan Pascanu ODL 65 4 0 16 Apr 2018
Aggregated Momentum: Stability Through Passive Damping James Lucas Shengyang Sun R. Zemel Roger C. Grosse 97 68 0 01 Apr 2018
Task Agnostic Continual Learning Using Online Variational Bayes Chen Zeno Itay Golan Elad Hoffer Daniel Soudry CLL FedML BDL 107 112 0 27 Mar 2018
Online Second Order Methods for Non-Convex Stochastic Optimizations Xi-Lin Li OffRL ODL 41 4 0 26 Mar 2018
On the insufficiency of existing momentum schemes for Stochastic Optimization Rahul Kidambi Praneeth Netrapalli Prateek Jain Sham Kakade ODL 98 120 0 15 Mar 2018
Understanding Short-Horizon Bias in Stochastic Meta-Optimization Yuhuai Wu Mengye Ren Renjie Liao Roger C. Grosse 115 138 0 06 Mar 2018
Accelerating Natural Gradient with Higher-Order Invariance Yang Song Jiaming Song Stefano Ermon 74 23 0 04 Mar 2018
Train Feedfoward Neural Network with Layer-wise Adaptive Rate via Approximating Back-matching Propagation Huishuai Zhang Wei-neng Chen Tie-Yan Liu 29 5 0 27 Feb 2018
Shampoo: Preconditioned Stochastic Tensor Optimization Vineet Gupta Tomer Koren Y. Singer ODL 115 226 0 26 Feb 2018