Structured Bayesian Pruning via Log-Normal Multiplicative Noise

20 May 2017

Dmitry Vetrov

Papers citing "Structured Bayesian Pruning via Log-Normal Multiplicative Noise"

34 / 34 papers shown

Title
A Bayesian Interpretation of Adaptive Low-Rank Adaptation Haolin Chen Philip N. Garner 58 1 0 16 Sep 2024
Cluster Generation via Deep Energy-Based Model A. Y. Artsukevich S. Lepeshkin 34 0 0 17 Jun 2022
Statistical Guarantees for Approximate Stationary Points of Simple Neural Networks Mahsa Taheri Fang Xie Johannes Lederer 31 0 0 09 May 2022
A Survey on Dropout Methods and Experimental Verification in Recommendation Yongqian Li Weizhi Ma C. L. Philip Chen Hao Fei Yiqun Liu Shaoping Ma Yue Yang 40 10 0 05 Apr 2022
Speedup deep learning models on GPU by taking advantage of efficient unstructured pruning and bit-width reduction Marcin Pietroñ Dominik Zurek 30 13 0 28 Dec 2021
MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge Geng Yuan Xiaolong Ma Wei Niu Zhengang Li Zhenglun Kong ... Minghai Qin Bin Ren Yanzhi Wang Sijia Liu Xue Lin 33 89 0 26 Oct 2021
Dynamic Neural Network Architectural and Topological Adaptation and Related Methods -- A Survey Lorenz Kummer AI4CE 45 0 0 28 Jul 2021
R-Drop: Regularized Dropout for Neural Networks Xiaobo Liang Lijun Wu Juntao Li Yue Wang Qi Meng Tao Qin Wei Chen Hao Fei Tie-Yan Liu 52 424 0 28 Jun 2021
DiffPrune: Neural Network Pruning with Deterministic Approximate Binary Gates and $L_0$ Regularization Yaniv Shulman 46 3 0 07 Dec 2020
Rethinking Weight Decay For Efficient Neural Network Pruning Hugo Tessier Vincent Gripon Mathieu Léonardon M. Arzel T. Hannagan David Bertrand 31 25 0 20 Nov 2020
Dynamic Hard Pruning of Neural Networks at the Edge of the Internet Lorenzo Valerio F. M. Nardini A. Passarella R. Perego 25 12 0 17 Nov 2020
Dirichlet Pruning for Neural Network Compression Kamil Adamczewski Mijung Park 27 3 0 10 Nov 2020
Neural Network Compression Via Sparse Optimization Tianyi Chen Bo Ji Yixin Shi Tianyu Ding Biyi Fang Sheng Yi Xiao Tu 36 15 0 10 Nov 2020
Principal Component Networks: Parameter Reduction Early in Training R. Waleffe Theodoros Rekatsinas 3DPC 19 9 0 23 Jun 2020
Adaptative Inference Cost With Convolutional Neural Mixture Models Adria Ruiz Jakob Verbeek VLM 30 22 0 19 Aug 2019
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems Anna Kuzina Evgenii Egorov Evgeny Burnaev MedIm 34 19 0 15 Aug 2019
Importance Estimation for Neural Network Pruning Pavlo Molchanov Arun Mallya Stephen Tyree I. Frosio Jan Kautz 3DPC 42 859 0 25 Jun 2019
Compressing RNNs for IoT devices by 15-38x using Kronecker Products Urmish Thakker Jesse G. Beu Dibakar Gope Chu Zhou Igor Fedorov Ganesh S. Dasika Matthew Mattina 27 36 0 07 Jun 2019
Training CNNs with Selective Allocation of Channels Jongheon Jeong Jinwoo Shin CVBM 41 15 0 11 May 2019
Play and Prune: Adaptive Filter Pruning for Deep Model Compression Pravendra Singh Vinay Kumar Verma Piyush Rai Vinay P. Namboodiri VLM 33 71 0 11 May 2019
Survey of Dropout Methods for Deep Neural Networks Alex Labach Hojjat Salehinejad S. Valaee 27 149 0 25 Apr 2019
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature Franz J. Király Bilal A. Mateen R. Sonabend 23 10 0 18 Dec 2018
Structured Pruning of Neural Networks with Budget-Aware Regularization Carl Lemaire Andrew Achkar Pierre-Marc Jodoin 27 92 0 23 Nov 2018
Multi-layer Pruning Framework for Compressing Single Shot MultiBox Detector Pravendra Singh Manikandan Ravikiran Neeraj Matiyali Vinay P. Namboodiri 33 21 0 20 Nov 2018
Sparse DNNs with Improved Adversarial Robustness Yiwen Guo Chao Zhang Changshui Zhang Yurong Chen AAML 25 151 0 23 Oct 2018
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network Xuanqing Liu Yao Li Chongruo Wu Cho-Jui Hsieh AAML OOD 24 171 0 01 Oct 2018
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors S. Ghosh Jiayu Yao Finale Doshi-Velez BDL UQCV 17 77 0 13 Jun 2018
Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking Haichuan Yang Yuhao Zhu Ji Liu CVBM 19 36 0 12 Jun 2018
Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation Manuel Haussmann Fred Hamprecht M. Kandemir BDL 33 6 0 19 May 2018
Nonparametric Bayesian Deep Networks with Local Competition Konstantinos P. Panousis S. Chatzis Sergios Theodoridis BDL 29 32 0 19 May 2018
Variance Networks: When Expectation Does Not Meet Your Expectations Kirill Neklyudov Dmitry Molchanov Arsenii Ashukha Dmitry Vetrov UQCV 22 23 0 10 Mar 2018
Synthesizing Neural Network Controllers with Probabilistic Model based Reinforcement Learning J. A. G. Higuera David Meger Gregory Dudek BDL 22 39 0 06 Mar 2018
Compressing Neural Networks using the Variational Information Bottleneck Bin Dai Chen Zhu David Wipf MLT 28 179 0 28 Feb 2018
Model Selection in Bayesian Neural Networks via Horseshoe Priors S. Ghosh Finale Doshi-Velez BDL 39 119 0 29 May 2017