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Bayesian Compression for Deep Learning

24 May 2017

Papers citing "Bayesian Compression for Deep Learning"

50 / 269 papers shown

Title
Dirichlet Pruning for Neural Network Compression Kamil Adamczewski Mijung Park 76 3 0 10 Nov 2020
Sparse within Sparse Gaussian Processes using Neighbor Information Gia-Lac Tran Dimitrios Milios Pietro Michiardi Maurizio Filippone 43 16 0 10 Nov 2020
Neural Network Compression Via Sparse Optimization Tianyi Chen Bo Ji Yixin Shi Tianyu Ding Biyi Fang Sheng Yi Xiao Tu 84 16 0 10 Nov 2020
Layer-adaptive sparsity for the Magnitude-based Pruning Jaeho Lee Sejun Park Sangwoo Mo SungSoo Ahn Jinwoo Shin 95 206 0 15 Oct 2020
Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win Utku Evci Yani Andrew Ioannou Cem Keskin Yann N. Dauphin 82 94 0 07 Oct 2020
A Survey on Deep Neural Network Compression: Challenges, Overview, and Solutions Rahul Mishra Hari Prabhat Gupta Tanima Dutta 66 93 0 05 Oct 2020
Handling of uncertainty in medical data using machine learning and probability theory techniques: A review of 30 years (1991-2020) R. Alizadehsani M. Roshanzamir Sadiq Hussain Abbas Khosravi Afsaneh Koohestani ... M. Panahiazar S. Nahavandi D. Srinivasan A. Atiya U. Acharya OOD 84 99 0 23 Aug 2020
Training Sparse Neural Networks using Compressed Sensing Jonathan W. Siegel Jianhong Chen Pengchuan Zhang Jinchao Xu 82 5 0 21 Aug 2020
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables Q. Wang H. V. Hoof BDL 72 42 0 21 Aug 2020
Towards Modality Transferable Visual Information Representation with Optimal Model Compression Rongqun Lin Linwei Zhu Shiqi Wang Sam Kwong 65 2 0 13 Aug 2020
Degree-Quant: Quantization-Aware Training for Graph Neural Networks Shyam A. Tailor Javier Fernandez-Marques Nicholas D. Lane GNN MQ 82 145 0 11 Aug 2020
Differentiable Joint Pruning and Quantization for Hardware Efficiency Ying Wang Yadong Lu Tijmen Blankevoort MQ 97 72 0 20 Jul 2020
VINNAS: Variational Inference-based Neural Network Architecture Search Martin Ferianc Hongxiang Fan Miguel R. D. Rodrigues 3DPC 176 6 0 12 Jul 2020
ESPN: Extremely Sparse Pruned Networks Minsu Cho Ameya Joshi Chinmay Hegde 56 9 0 28 Jun 2020
Topological Insights into Sparse Neural Networks Shiwei Liu T. Lee Anil Yaman Zahra Atashgahi David L. Ferraro Ghada Sokar Mykola Pechenizkiy Decebal Constantin Mocanu 68 30 0 24 Jun 2020
Slimming Neural Networks using Adaptive Connectivity Scores Madan Ravi Ganesh Dawsin Blanchard Jason J. Corso Salimeh Yasaei Sekeh 67 11 0 22 Jun 2020
An Overview of Neural Network Compression James OÑeill AI4CE 160 100 0 05 Jun 2020
Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks Meet P. Vadera B. Jalaeian Benjamin M. Marlin BDL FedML UQCV 69 20 0 16 May 2020
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors Michael W. Dusenberry Ghassen Jerfel Yeming Wen Yi-An Ma Jasper Snoek Katherine A. Heller Balaji Lakshminarayanan Dustin Tran UQCV BDL 107 215 0 14 May 2020
Bayesian Bits: Unifying Quantization and Pruning M. V. Baalen Christos Louizos Markus Nagel Rana Ali Amjad Ying Wang Tijmen Blankevoort Max Welling MQ 101 116 0 14 May 2020
Data-Free Network Quantization With Adversarial Knowledge Distillation Yoojin Choi Jihwan P. Choi Mostafa El-Khamy Jungwon Lee MQ 76 121 0 08 May 2020
Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T) Arturo Marbán Daniel Becking Simon Wiedemann Wojciech Samek MQ 51 12 0 02 Apr 2020
Information-Theoretic Probing with Minimum Description Length Elena Voita Ivan Titov 127 276 0 27 Mar 2020
Bayesian Sparsification Methods for Deep Complex-valued Networks Ivan Nazarov Evgeny Burnaev BDL 46 0 0 25 Mar 2020
BiDet: An Efficient Binarized Object Detector Ziwei Wang Ziyi Wu Jiwen Lu Jie Zhou MQ 125 66 0 09 Mar 2020
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 306 1,058 0 06 Mar 2020
Learned Threshold Pruning K. Azarian Yash Bhalgat Jinwon Lee Tijmen Blankevoort MQ 86 38 0 28 Feb 2020
Informative Bayesian Neural Network Priors for Weak Signals Tianyu Cui A. Havulinna Pekka Marttinen Samuel Kaski 67 9 0 24 Feb 2020
Communication-Efficient Edge AI: Algorithms and Systems Yuanming Shi Kai Yang Tao Jiang Jun Zhang Khaled B. Letaief GNN 101 335 0 22 Feb 2020
SYMOG: learning symmetric mixture of Gaussian modes for improved fixed-point quantization Lukas Enderich Fabian Timm Wolfram Burgard MQ 32 6 0 19 Feb 2020
DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving Wei Deng Junwei Pan Tian Zhou Deguang Kong Aaron Flores Guang Lin 34 4 0 17 Feb 2020
Lookahead: A Far-Sighted Alternative of Magnitude-based Pruning Sejun Park Jaeho Lee Sangwoo Mo Jinwoo Shin 65 94 0 12 Feb 2020
Soft Threshold Weight Reparameterization for Learnable Sparsity Aditya Kusupati Vivek Ramanujan Raghav Somani Mitchell Wortsman Prateek Jain Sham Kakade Ali Farhadi 211 247 0 08 Feb 2020
An Equivalence between Bayesian Priors and Penalties in Variational Inference Pierre Wolinski Guillaume Charpiat Yann Ollivier BDL 51 1 0 01 Feb 2020
A "Network Pruning Network" Approach to Deep Model Compression Vinay Kumar Verma Pravendra Singh Vinay P. Namboodiri Piyush Rai 3DPC VLM 58 8 0 15 Jan 2020
Resource-Efficient Neural Networks for Embedded Systems Wolfgang Roth Günther Schindler Lukas Pfeifenberger Robert Peharz Sebastian Tschiatschek Holger Fröning Franz Pernkopf Zoubin Ghahramani 92 51 0 07 Jan 2020
Taxonomy and Evaluation of Structured Compression of Convolutional Neural Networks Andrey Kuzmin Markus Nagel Saurabh Pitre Sandeep Pendyam Tijmen Blankevoort Max Welling 75 27 0 20 Dec 2019
Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning Samuel Kessler Vu Nguyen S. Zohren Stephen J. Roberts BDL 94 25 0 04 Dec 2019
Rodent: Relevance determination in differential equations Niklas Heim Václav vSmídl Tomávs Pevný 82 5 0 02 Dec 2019
Efficient Approximate Inference with Walsh-Hadamard Variational Inference Simone Rossi Sébastien Marmin Maurizio Filippone BDL 38 1 0 29 Nov 2019
Continual Learning with Adaptive Weights (CLAW) T. Adel Han Zhao Richard Turner CLL 76 73 0 21 Nov 2019
Structured Sparsification of Gated Recurrent Neural Networks E. Lobacheva Nadezhda Chirkova Alexander Markovich Dmitry Vetrov 67 3 0 13 Nov 2019
Iteratively Training Look-Up Tables for Network Quantization Fabien Cardinaux Stefan Uhlich K. Yoshiyama Javier Alonso García Lukas Mauch Stephen Tiedemann Thomas Kemp Akira Nakamura MQ 102 16 0 12 Nov 2019
Shrinkage with shrunken shoulders: Gibbs sampling shrinkage model posteriors with guaranteed convergence rates A. Nishimura M. Suchard 110 9 0 06 Nov 2019
Dynamic Regularizer with an Informative Prior Avinash Kori Manik Sharma 16 0 0 31 Oct 2019
Training DNN IoT Applications for Deployment On Analog NVM Crossbars F. García-Redondo Shidhartha Das G. Rosendale 55 5 0 30 Oct 2019
Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation Framework Srinidhi Hegde Ranjitha Prasad R. Hebbalaguppe Vishwajith Kumar 35 18 0 26 Oct 2019
An Adaptive Empirical Bayesian Method for Sparse Deep Learning Wei Deng Xiao Zhang F. Liang Guang Lin BDL 126 44 0 23 Oct 2019
Mirror Descent View for Neural Network Quantization Thalaiyasingam Ajanthan Kartik Gupta Philip Torr Leonid Sigal P. Dokania MQ 83 25 0 18 Oct 2019
Automatic Neural Network Compression by Sparsity-Quantization Joint Learning: A Constrained Optimization-based Approach Haichuan Yang Shupeng Gui Yuhao Zhu Ji Liu MQ 73 5 0 14 Oct 2019