Towards the Limit of Network Quantization

5 December 2016

Papers citing "Towards the Limit of Network Quantization"

24 / 24 papers shown

Title
GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance Jinuk Kim Marwa El Halabi W. Park Clemens JS Schaefer Deokjae Lee Yeonhong Park Jae W. Lee Hyun Oh Song MQ 29 0 0 11 May 2025
BackSlash: Rate Constrained Optimized Training of Large Language Models Jun Wu Jiangtao Wen Yuxing Han 34 0 0 23 Apr 2025
Object Motion Sensitivity: A Bio-inspired Solution to the Ego-motion Problem for Event-based Cameras Shay Snyder Hunter Thompson Md. Abdullah-Al Kaiser Gregory Schwartz Akhilesh R. Jaiswal Maryam Parsa 33 2 0 24 Mar 2023
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization Sanae Lotfi Marc Finzi Sanyam Kapoor Andres Potapczynski Micah Goldblum A. Wilson BDL MLT AI4CE 19 51 0 24 Nov 2022
HFedMS: Heterogeneous Federated Learning with Memorable Data Semantics in Industrial Metaverse Shenglai Zeng Zonghang Li Hongfang Yu Zhihao Zhang Long Luo Bo-wen Li Dusit Niyato 32 42 0 07 Nov 2022
Mixed-Precision Neural Networks: A Survey M. Rakka M. Fouda Pramod P. Khargonekar Fadi J. Kurdahi MQ 18 11 0 11 Aug 2022
Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications Deniz Gunduz Zhijin Qin Iñaki Estella Aguerri Harpreet S. Dhillon Zhaohui Yang Aylin Yener Kai‐Kit Wong C. Chae 16 431 0 19 Jul 2022
Low-rank Tensor Decomposition for Compression of Convolutional Neural Networks Using Funnel Regularization Bo-Shiuan Chu Che-Rung Lee 18 11 0 07 Dec 2021
Multi-Glimpse Network: A Robust and Efficient Classification Architecture based on Recurrent Downsampled Attention S. Tan Runpei Dong Kaisheng Ma 22 2 0 03 Nov 2021
Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes Sanghyun Hong Michael-Andrei Panaitescu-Liess Yigitcan Kaya Tudor Dumitras MQ 52 13 0 26 Oct 2021
Training Deep Neural Networks with Joint Quantization and Pruning of Weights and Activations Xinyu Zhang Ian Colbert Ken Kreutz-Delgado Srinjoy Das MQ 24 11 0 15 Oct 2021
Compacting Deep Neural Networks for Internet of Things: Methods and Applications Ke Zhang Hanbo Ying Hongning Dai Lin Li Yuangyuang Peng Keyi Guo Hongfang Yu 16 38 0 20 Mar 2021
Fixed-point Quantization of Convolutional Neural Networks for Quantized Inference on Embedded Platforms Rishabh Goyal Joaquin Vanschoren V. V. Acht S. Nijssen MQ 14 23 0 03 Feb 2021
A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects Zewen Li Wenjie Yang Shouheng Peng Fan Liu HAI 3DV 54 2,595 0 01 Apr 2020
A Survey of Methods for Low-Power Deep Learning and Computer Vision Abhinav Goel Caleb Tung Yung-Hsiang Lu George K. Thiruvathukal VLM 10 92 0 24 Mar 2020
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 19 18 0 27 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 41 92 0 27 Jul 2019
And the Bit Goes Down: Revisiting the Quantization of Neural Networks Pierre Stock Armand Joulin Rémi Gribonval Benjamin Graham Hervé Jégou MQ 29 149 0 12 Jul 2019
A Targeted Acceleration and Compression Framework for Low bit Neural Networks Biao Qian Yang Wang MQ 21 0 0 09 Jul 2019
Quantization for Rapid Deployment of Deep Neural Networks J. Lee Sangwon Ha Saerom Choi Won-Jo Lee Seungwon Lee MQ 14 48 0 12 Oct 2018
Rate Distortion For Model Compression: From Theory To Practice Weihao Gao Yu-Han Liu Chong-Jun Wang Sewoong Oh 25 31 0 09 Oct 2018
A Survey on Methods and Theories of Quantized Neural Networks Yunhui Guo MQ 27 230 0 13 Aug 2018
BitNet: Bit-Regularized Deep Neural Networks Aswin Raghavan Mohamed R. Amer S. Chai Graham Taylor MQ 27 10 0 16 Aug 2017
ShiftCNN: Generalized Low-Precision Architecture for Inference of Convolutional Neural Networks Denis A. Gudovskiy Luca Rigazio MQ 19 52 0 07 Jun 2017