And the Bit Goes Down: Revisiting the Quantization of Neural Networks

12 July 2019

Pierre Stock

Armand Joulin

Rémi Gribonval

Benjamin Graham

Hervé Jégou

ArXiv PDF HTML

Papers citing "And the Bit Goes Down: Revisiting the Quantization of Neural Networks"

33 / 33 papers shown

Title
An Empirical Investigation of Matrix Factorization Methods for Pre-trained Transformers Ashim Gupta Sina Mahdipour Saravani P. Sadayappan Vivek Srikumar 35 2 0 17 Jun 2024
GPTVQ: The Blessing of Dimensionality for LLM Quantization M. V. Baalen Andrey Kuzmin Markus Nagel Peter Couperus Cédric Bastoul E. Mahurin Tijmen Blankevoort Paul N. Whatmough MQ 34 28 0 23 Feb 2024
eDKM: An Efficient and Accurate Train-time Weight Clustering for Large Language Models Minsik Cho Keivan Alizadeh Vahid Qichen Fu Saurabh N. Adya C. C. D. Mundo Mohammad Rastegari Devang Naik Peter Zatloukal MQ 23 6 0 02 Sep 2023
Self-Distilled Quantization: Achieving High Compression Rates in Transformer-Based Language Models James OÑeill Sourav Dutta VLM MQ 40 1 0 12 Jul 2023
PQA: Exploring the Potential of Product Quantization in DNN Hardware Acceleration Ahmed F. AbouElhamayed Angela Cui Javier Fernandez-Marques Nicholas D. Lane Mohamed S. Abdelfattah MQ 23 4 0 25 May 2023
NIRVANA: Neural Implicit Representations of Videos with Adaptive Networks and Autoregressive Patch-wise Modeling Shishira R. Maiya Sharath Girish Max Ehrlich Hanyu Wang Kwot Sin Lee Patrick Poirson Pengxiang Wu Chen Wang Abhinav Shrivastava VGen 47 40 0 30 Dec 2022
Hyperspherical Quantization: Toward Smaller and More Accurate Models Dan Liu X. Chen Chen-li Ma Xue Liu MQ 30 3 0 24 Dec 2022
Weight Fixing Networks Christopher Subia-Waud S. Dasmahapatra MQ 14 2 0 24 Oct 2022
Deep learning model compression using network sensitivity and gradients M. Sakthi N. Yadla Raj Pawate 21 2 0 11 Oct 2022
Look-ups are not (yet) all you need for deep learning inference Calvin McCarter Nicholas Dronen 21 4 0 12 Jul 2022
LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification Sharath Girish Kamal Gupta Saurabh Singh Abhinav Shrivastava 36 11 0 06 Apr 2022
Neural Network Quantization with AI Model Efficiency Toolkit (AIMET) S. Siddegowda Marios Fournarakis Markus Nagel Tijmen Blankevoort Chirag I. Patel Abhijit Khobare MQ 12 31 0 20 Jan 2022
Implicit Neural Video Compression Yunfan Zhang T. V. Rozendaal Johann Brehmer Markus Nagel Taco S. Cohen 49 57 0 21 Dec 2021
LegoDNN: Block-grained Scaling of Deep Neural Networks for Mobile Vision Rui Han Qinglong Zhang C. Liu Guoren Wang Jian Tang L. Chen 21 43 0 18 Dec 2021
Toward Compact Parameter Representations for Architecture-Agnostic Neural Network Compression Yuezhou Sun Wenlong Zhao Lijun Zhang Xiao Liu Hui Guan Matei A. Zaharia 26 0 0 19 Nov 2021
LVAC: Learned Volumetric Attribute Compression for Point Clouds using Coordinate Based Networks Berivan Isik P. Chou S. Hwang Nick Johnston G. Toderici 3DPC 31 28 0 17 Nov 2021
RED++ : Data-Free Pruning of Deep Neural Networks via Input Splitting and Output Merging Edouard Yvinec Arnaud Dapogny Matthieu Cord Kévin Bailly 28 15 0 30 Sep 2021
A New Clustering-Based Technique for the Acceleration of Deep Convolutional Networks Erion-Vasilis M. Pikoulis C. Mavrokefalidis Aris S. Lalos 24 10 0 19 Jul 2021
A White Paper on Neural Network Quantization Markus Nagel Marios Fournarakis Rana Ali Amjad Yelysei Bondarenko M. V. Baalen Tijmen Blankevoort MQ 24 504 0 15 Jun 2021
Pre-Trained Models: Past, Present and Future Xu Han Zhengyan Zhang Ning Ding Yuxian Gu Xiao Liu ... Jie Tang Ji-Rong Wen Jinhui Yuan Wayne Xin Zhao Jun Zhu AIFin MQ AI4MH 40 815 0 14 Jun 2021
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training Jianfei Chen Lianmin Zheng Z. Yao Dequan Wang Ion Stoica Michael W. Mahoney Joseph E. Gonzalez MQ 27 74 0 29 Apr 2021
Differentiable Model Compression via Pseudo Quantization Noise Alexandre Défossez Yossi Adi Gabriel Synnaeve DiffM MQ 18 47 0 20 Apr 2021
Knowledge Distillation as Semiparametric Inference Tri Dao G. Kamath Vasilis Syrgkanis Lester W. Mackey 37 31 0 20 Apr 2021
VS-Quant: Per-vector Scaled Quantization for Accurate Low-Precision Neural Network Inference Steve Dai Rangharajan Venkatesan Haoxing Ren B. Zimmer W. Dally Brucek Khailany MQ 25 67 0 08 Feb 2021
Fixed-point Quantization of Convolutional Neural Networks for Quantized Inference on Embedded Platforms Rishabh Goyal Joaquin Vanschoren V. V. Acht S. Nijssen MQ 22 23 0 03 Feb 2021
Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks Julieta Martinez Jashan Shewakramani Ting Liu Ioan Andrei Bârsan Wenyuan Zeng R. Urtasun MQ 18 30 0 29 Oct 2020
TernaryBERT: Distillation-aware Ultra-low Bit BERT Wei Zhang Lu Hou Yichun Yin Lifeng Shang Xiao Chen Xin Jiang Qun Liu MQ 30 208 0 27 Sep 2020
Transform Quantization for CNN (Convolutional Neural Network) Compression Sean I. Young Wang Zhe David S. Taubman B. Girod MQ 29 69 0 02 Sep 2020
SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloud Stefanos Laskaridis Stylianos I. Venieris Mario Almeida Ilias Leontiadis Nicholas D. Lane 28 265 0 14 Aug 2020
FrostNet: Towards Quantization-Aware Network Architecture Search Taehoon Kim Y. Yoo Jihoon Yang MQ 22 2 0 17 Jun 2020
An Overview of Neural Network Compression James OÑeill AI4CE 45 98 0 05 Jun 2020
BiQGEMM: Matrix Multiplication with Lookup Table For Binary-Coding-based Quantized DNNs Yongkweon Jeon Baeseong Park S. Kwon Byeongwook Kim Jeongin Yun Dongsoo Lee MQ 27 30 0 20 May 2020
Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights Aojun Zhou Anbang Yao Yiwen Guo Lin Xu Yurong Chen MQ 337 1,049 0 10 Feb 2017