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Universal Deep Neural Network Compression

7 February 2018

Papers citing "Universal Deep Neural Network Compression"

33 / 33 papers shown

Title
A Novel Structure-Agnostic Multi-Objective Approach for Weight-Sharing Compression in Deep Neural Networks Rasa Khosrowshahli Shahryar Rahnamayan Beatrice Ombuki-Berman MQ 76 1 0 06 Jan 2025
Resource-Limited Automated Ki67 Index Estimation in Breast Cancer J. Gliozzo Giosuè Cataldo Marinò A. Bonometti Marco Frasca Dario Malchiodi 52 0 0 22 Dec 2023
FedSZ: Leveraging Error-Bounded Lossy Compression for Federated Learning Communications Grant Wilkins Sheng Di Jon C. Calhoun Zilinghan Li Kibaek Kim Robert Underwood Richard Mortier Franck Cappello FedML 82 4 0 20 Dec 2023
LL-VQ-VAE: Learnable Lattice Vector-Quantization For Efficient Representations Ahmed Khalil Robert Piechocki Raúl Santos-Rodríguez 54 2 0 13 Oct 2023
Divide-and-Conquer the NAS puzzle in Resource Constrained Federated Learning Systems Yeshwanth Venkatesha Youngeun Kim Hyoungseob Park Priyadarshini Panda FedML 45 4 0 11 May 2023
Low Rank Optimization for Efficient Deep Learning: Making A Balance between Compact Architecture and Fast Training Xinwei Ou Zhangxin Chen Ce Zhu Yipeng Liu 79 5 0 22 Mar 2023
Deep learning model compression using network sensitivity and gradients M. Sakthi N. Yadla Raj Pawate 58 2 0 11 Oct 2022
Supervised Robustness-preserving Data-free Neural Network Pruning Mark Huasong Meng Guangdong Bai Sin Gee Teo Jin Song Dong AAML 96 4 0 02 Apr 2022
Croesus: Multi-Stage Processing and Transactions for Video-Analytics in Edge-Cloud Systems Samaa Gazzaz Vishal Chakraborty Faisal Nawab 48 10 0 31 Dec 2021
Deep Odometry Systems on Edge with EKF-LoRa Backend for Real-Time Positioning in Adverse Environment Zhuangzhuang Dai Muhamad Risqi U. Saputra Chris Xiaoxuan Lu Andrew Markham A. Trigoni 62 1 0 10 Dec 2021
Training Deep Neural Networks with Joint Quantization and Pruning of Weights and Activations Xinyu Zhang Ian Colbert Ken Kreutz-Delgado Srinjoy Das MQ 100 12 0 15 Oct 2021
Compact representations of convolutional neural networks via weight pruning and quantization Giosuè Cataldo Marinò A. Petrini D. Malchiodi Marco Frasca MQ 23 4 0 28 Aug 2021
DKM: Differentiable K-Means Clustering Layer for Neural Network Compression Minsik Cho Keivan Alizadeh Vahid Saurabh N. Adya Mohammad Rastegari 95 34 0 28 Aug 2021
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety Sebastian Houben Stephanie Abrecht Maram Akila Andreas Bär Felix Brockherde ... Serin Varghese Michael Weber Sebastian J. Wirkert Tim Wirtz Matthias Woehrle AAML 130 58 0 29 Apr 2021
An Information-Theoretic Justification for Model Pruning Berivan Isik Tsachy Weissman Albert No 164 37 0 16 Feb 2021
Neural Network Compression for Noisy Storage Devices Berivan Isik Kristy Choi Xin-Yang Zheng Tsachy Weissman Stefano Ermon H. P. Wong Armin Alaghi 70 13 0 15 Feb 2021
Compression strategies and space-conscious representations for deep neural networks Giosuè Cataldo Marinò G. Ghidoli Marco Frasca D. Malchiodi 27 10 0 15 Jul 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
PERMDNN: Efficient Compressed DNN Architecture with Permuted Diagonal Matrices Chunhua Deng Siyu Liao Yi Xie Keshab K. Parhi Xuehai Qian Bo Yuan 86 93 0 23 Apr 2020
Trends and Advancements in Deep Neural Network Communication Felix Sattler Thomas Wiegand Wojciech Samek GNN 72 9 0 06 Mar 2020
Variable Rate Deep Image Compression With a Conditional Autoencoder Yoojin Choi Mostafa El-Khamy Jungwon Lee DRL 94 227 0 11 Sep 2019
DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks Simon Wiedemann H. Kirchhoffer Stefan Matlage Paul Haase Arturo Marbán ... Ahmed Osman D. Marpe H. Schwarz Thomas Wiegand Wojciech Samek 111 98 0 27 Jul 2019
HadaNets: Flexible Quantization Strategies for Neural Networks Yash Akhauri MQ 38 7 0 26 May 2019
Compressibility Loss for Neural Network Weights Çağlar Aytekin Francesco Cricri Emre B. Aksu 48 11 0 03 May 2019
Jointly Sparse Convolutional Neural Networks in Dual Spatial-Winograd Domains Yoojin Choi Mostafa El-Khamy Jungwon Lee 44 6 0 21 Feb 2019
Artificial neural networks condensation: A strategy to facilitate adaption of machine learning in medical settings by reducing computational burden Dianbo Liu N. Sepulveda Ming Zheng 68 7 0 23 Dec 2018
Entropy-Constrained Training of Deep Neural Networks Simon Wiedemann Arturo Marbán K. Müller Wojciech Samek 84 29 0 18 Dec 2018
Learning Sparse Low-Precision Neural Networks With Learnable Regularization Yoojin Choi Mostafa El-Khamy Jungwon Lee MQ 66 31 0 01 Sep 2018
TFLMS: Large Model Support in TensorFlow by Graph Rewriting Tung D. Le Haruki Imai Yasushi Negishi K. Kawachiya GNN 104 47 0 05 Jul 2018
GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking Patrick H. Chen Si Si Yang Li Ciprian Chelba Cho-Jui Hsieh 67 70 0 18 Jun 2018
Compact and Computationally Efficient Representation of Deep Neural Networks Simon Wiedemann K. Müller Wojciech Samek MQ 87 71 0 27 May 2018
Compression of Deep Convolutional Neural Networks under Joint Sparsity Constraints Yoojin Choi Mostafa El-Khamy Jungwon Lee 40 6 0 21 May 2018
Low-memory convolutional neural networks through incremental depth-first processing Jonathan Binas Yoshua Bengio SupR 41 3 0 28 Apr 2018