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Training Structured Neural Networks Through Manifold Identification and Variance Reduction

5 December 2021

Papers citing "Training Structured Neural Networks Through Manifold Identification and Variance Reduction"

28 / 28 papers shown

Title
[Reproducibility Report] Rigging the Lottery: Making All Tickets Winners Varun Sundar Rajat Vadiraj Dwaraknath 40 5 0 29 Mar 2021
Structured Sparsity Inducing Adaptive Optimizers for Deep Learning T. Deleu Yoshua Bengio ODL 66 23 0 07 Feb 2021
Dual Averaging is Surprisingly Effective for Deep Learning Optimization Samy Jelassi Aaron Defazio 54 5 0 20 Oct 2020
A General Family of Stochastic Proximal Gradient Methods for Deep Learning Jihun Yun A. Lozano Eunho Yang 60 13 0 15 Jul 2020
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 286 1,055 0 06 Mar 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 580 42,677 0 03 Dec 2019
Rigging the Lottery: Making All Tickets Winners Utku Evci Trevor Gale Jacob Menick Pablo Samuel Castro Erich Elsen 201 607 0 25 Nov 2019
Momentum-Based Variance Reduction in Non-Convex SGD Ashok Cutkosky Francesco Orabona ODL 98 410 0 24 May 2019
Hybrid Stochastic Gradient Descent Algorithms for Stochastic Nonconvex Optimization Quoc Tran-Dinh Nhan H. Pham Dzung Phan Lam M. Nguyen 79 56 0 15 May 2019
The State of Sparsity in Deep Neural Networks Trevor Gale Erich Elsen Sara Hooker 167 763 0 25 Feb 2019
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization Nhan H. Pham Lam M. Nguyen Dzung Phan Quoc Tran-Dinh 77 141 0 15 Feb 2019
On the Ineffectiveness of Variance Reduced Optimization for Deep Learning Aaron Defazio Léon Bottou UQCV DRL 82 113 0 11 Dec 2018
Inexact SARAH Algorithm for Stochastic Optimization Lam M. Nguyen K. Scheinberg Martin Takáč 82 51 0 25 Nov 2018
ProxQuant: Quantized Neural Networks via Proximal Operators Yu Bai Yu Wang Edo Liberty MQ 86 117 0 01 Oct 2018
Learning Intrinsic Sparse Structures within Long Short-Term Memory W. Wen Yuxiong He Samyam Rajbhandari Minjia Zhang Wenhan Wang Fang Liu Bin Hu Yiran Chen H. Li MQ 121 142 0 15 Sep 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 289 8,928 0 25 Aug 2017
Asymptotic Optimality in Stochastic Optimization John C. Duchi Feng Ruan 92 63 0 16 Dec 2016
Loss-aware Binarization of Deep Networks Lu Hou Quanming Yao James T. Kwok MQ 81 220 0 05 Nov 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 884 36,910 0 25 Aug 2016
Learning Structured Sparsity in Deep Neural Networks W. Wen Chunpeng Wu Yandan Wang Yiran Chen Hai Helen Li 199 2,341 0 12 Aug 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.3K 194,641 0 10 Dec 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 471 43,357 0 11 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,433 0 22 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,575 0 04 Sep 2014
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 139 1,830 0 01 Jul 2014
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 163 741 0 19 Mar 2014
Nearly unbiased variable selection under minimax concave penalty Cun-Hui Zhang 344 3,570 0 25 Feb 2010
A note on the group lasso and a sparse group lasso J. Friedman Trevor Hastie Robert Tibshirani 234 839 0 05 Jan 2010