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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
Mirror descent of Hopfield model Hyungjoon Soh D. Kim Juno Hwang Junghyo Jo 74 0 0 29 Nov 2022
Exploring Temporal Information Dynamics in Spiking Neural Networks Youngeun Kim Yuhang Li Hyoungseob Park Yeshwanth Venkatesha Anna Hambitzer Priyadarshini Panda 93 35 0 26 Nov 2022
PipeFisher: Efficient Training of Large Language Models Using Pipelining and Fisher Information Matrices Kazuki Osawa Shigang Li Torsten Hoefler AI4CE 84 26 0 25 Nov 2022
A Self-Attention Ansatz for Ab-initio Quantum Chemistry Ingrid von Glehn J. Spencer David Pfau 69 68 0 24 Nov 2022
Integral Continual Learning Along the Tangent Vector Field of Tasks Tianlin Liu Aditya Golatkar Stefano Soatto Alessandro Achille CLL 69 3 0 23 Nov 2022
Understanding Sparse Feature Updates in Deep Networks using Iterative Linearisation Adrian Goldwaser Hong Ge MLT 27 0 0 22 Nov 2022
VeLO: Training Versatile Learned Optimizers by Scaling Up Luke Metz James Harrison C. Freeman Amil Merchant Lucas Beyer ... Naman Agrawal Ben Poole Igor Mordatch Adam Roberts Jascha Narain Sohl-Dickstein 140 60 0 17 Nov 2022
Black Box Lie Group Preconditioners for SGD Xi-Lin Li 59 9 0 08 Nov 2022
Geometry and convergence of natural policy gradient methods Johannes Muller Guido Montúfar 97 12 0 03 Nov 2022
Elastic Weight Consolidation Improves the Robustness of Self-Supervised Learning Methods under Transfer Andrius Ovsianas Jason Ramapuram Dan Busbridge Eeshan Gunesh Dhekane Russ Webb 29 4 0 28 Oct 2022
Adaptive scaling of the learning rate by second order automatic differentiation F. Gournay Alban Gossard ODL 55 2 0 26 Oct 2022
Federated Learning and Meta Learning: Approaches, Applications, and Directions Xiaonan Liu Yansha Deng Arumugam Nallanathan M. Bennis 125 40 0 24 Oct 2022
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning Zhijie Deng Feng Zhou Jun Zhu BDL 83 19 0 23 Oct 2022
HesScale: Scalable Computation of Hessian Diagonals Mohamed Elsayed A. R. Mahmood 85 8 0 20 Oct 2022
Brand New K-FACs: Speeding up K-FAC with Online Decomposition Updates C. Puiu 32 2 0 16 Oct 2022
Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities Brian Bartoldson B. Kailkhura Davis W. Blalock 113 51 0 13 Oct 2022
Component-Wise Natural Gradient Descent -- An Efficient Neural Network Optimization Tran van Sang Mhd Irvan R. Yamaguchi Toshiyuki Nakata 66 1 0 11 Oct 2022
Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach Peng Mi Li Shen Tianhe Ren Yiyi Zhou Xiaoshuai Sun Rongrong Ji Dacheng Tao AAML 123 72 0 11 Oct 2022
Learning to Optimize Quasi-Newton Methods Isaac Liao Rumen Dangovski Jakob N. Foerster Marin Soljacic 92 4 0 11 Oct 2022
Sampling-based inference for large linear models, with application to linearised Laplace Javier Antorán Shreyas Padhy Riccardo Barbano Eric T. Nalisnick David Janz José Miguel Hernández-Lobato BDL 53 17 0 10 Oct 2022
Rethinking Normalization Methods in Federated Learning Zhixu Du Jingwei Sun Ang Li Pin-Yu Chen Jianyi Zhang H. Li Yiran Chen FedML 65 31 0 07 Oct 2022
Reinforcement Learning Algorithms: An Overview and Classification Fadi AlMahamid Katarina Grolinger 39 45 0 29 Sep 2022
Random initialisations performing above chance and how to find them Frederik Benzing Simon Schug Robert Meier J. Oswald Yassir Akram Nicolas Zucchet Laurence Aitchison Angelika Steger ODL 119 26 0 15 Sep 2022
Efficient first-order predictor-corrector multiple objective optimization for fair misinformation detection Eric Enouen Katja Mathesius Sean Wang Arielle K. Carr Sihong Xie 51 2 0 15 Sep 2022
Training Neural Networks in Single vs Double Precision T. Hrycej Bernhard Bermeitinger Siegfried Handschuh 28 4 0 15 Sep 2022
Deep Variational Free Energy Approach to Dense Hydrogen H.-j. Xie Ziqun Li Han Wang Linfeng Zhang Lei Wang 92 9 0 13 Sep 2022
If Influence Functions are the Answer, Then What is the Question? Juhan Bae Nathan Ng Alston Lo Marzyeh Ghassemi Roger C. Grosse TDI 124 104 0 12 Sep 2022
Ab-initio quantum chemistry with neural-network wavefunctions J. Hermann J. Spencer Kenny Choo Antonio Mezzacapo W. Foulkes David Pfau Giuseppe Carleo Frank Noé AI4CE 83 86 0 26 Aug 2022
Autonomous Unmanned Aerial Vehicle Navigation using Reinforcement Learning: A Systematic Review Fadi AlMahamid Katarina Grolinger 63 76 0 25 Aug 2022
Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning Elias Frantar Sidak Pal Singh Dan Alistarh MQ 147 245 0 24 Aug 2022
DLCFT: Deep Linear Continual Fine-Tuning for General Incremental Learning Hyounguk Shon Janghyeon Lee Seungwook Kim Junmo Kim CLL 67 12 0 17 Aug 2022
Training Overparametrized Neural Networks in Sublinear Time Yichuan Deng Han Hu Zhao Song Omri Weinstein Danyang Zhuo BDL 99 28 0 09 Aug 2022
Improving the Trainability of Deep Neural Networks through Layerwise Batch-Entropy Regularization David Peer Bart Keulen Sebastian Stabinger J. Piater A. Rodríguez-Sánchez 46 6 0 01 Aug 2022
Adaptive Second Order Coresets for Data-efficient Machine Learning Omead Brandon Pooladzandi David Davini Baharan Mirzasoleiman 105 65 0 28 Jul 2022
Riemannian Natural Gradient Methods Jiang Hu Ruicheng Ao Anthony Man-Cho So Minghan Yang Zaiwen Wen 67 11 0 15 Jul 2022
PoF: Post-Training of Feature Extractor for Improving Generalization Ikuro Sato Ryota Yamada Masayuki Tanaka Nakamasa Inoue Rei Kawakami 39 4 0 05 Jul 2022
Randomized K-FACs: Speeding up K-FAC with Randomized Numerical Linear Algebra C. Puiu 56 2 0 30 Jun 2022
Scalable K-FAC Training for Deep Neural Networks with Distributed Preconditioning Lin Zhang Shaoshuai Shi Wei Wang Yue Liu 70 10 0 30 Jun 2022
Laplacian Autoencoders for Learning Stochastic Representations M. Miani Frederik Warburg Pablo Moreno-Muñoz Nicke Skafte Detlefsen Søren Hauberg UQCV BDL SSL 79 11 0 30 Jun 2022
Positive-definite parametrization of mixed quantum states with deep neural networks F. Vicentini R. Rossi Giuseppe Carleo 36 14 0 27 Jun 2022
Robustness to corruption in pre-trained Bayesian neural networks Xi Wang Laurence Aitchison OOD UQCV 69 5 0 24 Jun 2022
Cold Posteriors through PAC-Bayes Konstantinos Pitas Julyan Arbel 96 5 0 22 Jun 2022
Information Geometry of Dropout Training Masanari Kimura H. Hino 46 2 0 22 Jun 2022
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning Javier Antorán David Janz J. Allingham Erik A. Daxberger Riccardo Barbano Eric T. Nalisnick José Miguel Hernández-Lobato UQCV BDL 96 31 0 17 Jun 2022
Fast Finite Width Neural Tangent Kernel Roman Novak Jascha Narain Sohl-Dickstein S. Schoenholz AAML 67 56 0 17 Jun 2022
Faster Optimization on Sparse Graphs via Neural Reparametrization Nima Dehmamy C. Both J. Long Rose Yu 56 1 0 26 May 2022
$O(N^2)$ Universal Antisymmetry in Fermionic Neural Networks Tianyu Pang Shuicheng Yan Min Lin 57 3 0 26 May 2022
Understanding Programmatic Weak Supervision via Source-aware Influence Function Jieyu Zhang Hong Wang Cheng-Yu Hsieh Alexander Ratner TDI 88 12 0 25 May 2022
Symmetry Teleportation for Accelerated Optimization B. Zhao Nima Dehmamy Robin Walters Rose Yu ODL 109 24 0 21 May 2022
Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need? Leon Gerard Michael Scherbela P. Marquetand Philipp Grohs AI4CE 75 37 0 19 May 2022