Training and Inference with Integers in Deep Neural Networks

13 February 2018

Papers citing "Training and Inference with Integers in Deep Neural Networks"

50 / 153 papers shown

Title
NeuroSim V1.5: Improved Software Backbone for Benchmarking Compute-in-Memory Accelerators with Device and Circuit-level Non-idealities James Read Ming-Yen Lee Wei-Hsing Huang Yuan-Chun Luo A. Lu Shimeng Yu 34 0 0 05 May 2025
Silenzio: Secure Non-Interactive Outsourced MLP Training Jonas Sander T. Eisenbarth 33 0 0 24 Apr 2025
Tin-Tin: Towards Tiny Learning on Tiny Devices with Integer-based Neural Network Training Yi Hu Jinhang Zuo Eddie Zhang Bob Iannucci Carlee Joe-Wong 37 0 0 13 Apr 2025
PRIOT: Pruning-Based Integer-Only Transfer Learning for Embedded Systems Honoka Anada Sefutsu Ryu Masayuki Usui Tatsuya Kaneko Shinya Takamaeda-Yamazaki 52 1 0 21 Mar 2025
GSQ-Tuning: Group-Shared Exponents Integer in Fully Quantized Training for LLMs On-Device Fine-tuning Sifan Zhou Shuo Wang Zhihang Yuan Mingjia Shi Yuzhang Shang Dawei Yang ALM MQ 90 0 0 18 Feb 2025
MICSim: A Modular Simulator for Mixed-signal Compute-in-Memory based AI Accelerator Cong Wang Zeming Chen Shanshi Huang 24 1 0 23 Sep 2024
Art and Science of Quantizing Large-Scale Models: A Comprehensive Overview Yanshu Wang Tong Yang Xiyan Liang Guoan Wang Hanning Lu Xu Zhe Yaoming Li Li Weitao MQ 42 3 0 18 Sep 2024
On Exact Bit-level Reversible Transformers Without Changing Architectures Guoqiang Zhang J. P. Lewis W. Kleijn MQ AI4CE 32 0 0 12 Jul 2024
FLoCoRA: Federated learning compression with low-rank adaptation Lucas Grativol Ribeiro Mathieu Léonardon Guillaume Muller Virginie Fresse Matthieu Arzel AI4CE 37 1 0 20 Jun 2024
Collage: Light-Weight Low-Precision Strategy for LLM Training Tao Yu Gaurav Gupta Karthick Gopalswamy Amith R. Mamidala Hao Zhou Jeffrey Huynh Youngsuk Park Ron Diamant Anoop Deoras Jun Huan MQ 59 3 0 06 May 2024
IM-Unpack: Training and Inference with Arbitrarily Low Precision Integers Zhanpeng Zeng Karthikeyan Sankaralingam Vikas Singh 58 1 0 12 Mar 2024
Neural Network Training on Encrypted Data with TFHE Luis Montero Jordan Fréry Celia Kherfallah Roman Bredehoft Andrei Stoian FedML 25 2 0 29 Jan 2024
Exploring Highly Quantised Neural Networks for Intrusion Detection in Automotive CAN Shashwat Khandelwal Shanker Shreejith 18 0 0 19 Jan 2024
Real-Time Zero-Day Intrusion Detection System for Automotive Controller Area Network on FPGAs Shashwat Khandelwal Shanker Shreejith AAML 11 2 0 19 Jan 2024
A Lightweight FPGA-based IDS-ECU Architecture for Automotive CAN Shashwat Khandelwal Shanker Shreejith 9 13 0 19 Jan 2024
A Lightweight Multi-Attack CAN Intrusion Detection System on Hybrid FPGAs Shashwat Khandelwal Shanker Shreejith 15 11 0 19 Jan 2024
Deep Learning-based Embedded Intrusion Detection System for Automotive CAN Shashwat Khandelwal Eashan Wadhwa Shanker Shreejith 11 8 0 19 Jan 2024
Mixed-Precision Quantization for Federated Learning on Resource-Constrained Heterogeneous Devices Huancheng Chen H. Vikalo FedML MQ 16 7 0 29 Nov 2023
PIPE : Parallelized Inference Through Post-Training Quantization Ensembling of Residual Expansions Edouard Yvinec Arnaud Dapogny Kévin Bailly MQ 15 0 0 27 Nov 2023
Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference? Cheng Zhang Jianyi Cheng Ilia Shumailov George A. Constantinides Yiren Zhao MQ 21 9 0 08 Oct 2023
Designing strong baselines for ternary neural network quantization through support and mass equalization Edouard Yvinec Arnaud Dapogny Kévin Bailly MQ 25 0 0 30 Jun 2023
Training Transformers with 4-bit Integers Haocheng Xi Changhao Li Jianfei Chen Jun Zhu MQ 25 47 0 21 Jun 2023
SlimFit: Memory-Efficient Fine-Tuning of Transformer-based Models Using Training Dynamics A. Ardakani Altan Haan Shangyin Tan Doru-Thom Popovici Alvin Cheung Costin Iancu Koushik Sen 16 2 0 29 May 2023
Standalone 16-bit Neural Network Training: Missing Study for Hardware-Limited Deep Learning Practitioners Juyoung Yun Byungkon Kang Francois Rameau Zhoulai Fu Zhoulai Fu MQ 18 1 0 18 May 2023
Mathematical Challenges in Deep Learning V. Nia Guojun Zhang I. Kobyzev Michael R. Metel Xinlin Li ... S. Hemati M. Asgharian Linglong Kong Wulong Liu Boxing Chen AI4CE VLM 37 1 0 24 Mar 2023
Towards Optimal Compression: Joint Pruning and Quantization Ben Zandonati Glenn Bucagu Adrian Alan Pol M. Pierini Olya Sirkin Tal Kopetz MQ 22 2 0 15 Feb 2023
Data Quality-aware Mixed-precision Quantization via Hybrid Reinforcement Learning Yingchun Wang Jingcai Guo Song Guo Weizhan Zhang MQ 31 20 0 09 Feb 2023
Training with Mixed-Precision Floating-Point Assignments Wonyeol Lee Rahul Sharma A. Aiken MQ 24 2 0 31 Jan 2023
The Hidden Power of Pure 16-bit Floating-Point Neural Networks Juyoung Yun Byungkon Kang Zhoulai Fu MQ 26 1 0 30 Jan 2023
MobileTL: On-device Transfer Learning with Inverted Residual Blocks HungYueh Chiang N. Frumkin Feng Liang Diana Marculescu MQ 32 12 0 05 Dec 2022
POLICE: Provably Optimal Linear Constraint Enforcement for Deep Neural Networks Randall Balestriero Yann LeCun 14 15 0 02 Nov 2022
Verifiable and Energy Efficient Medical Image Analysis with Quantised Self-attentive Deep Neural Networks Rakshith Sathish S. Khare Debdoot Sheet 39 4 0 30 Sep 2022
Mixed-Precision Neural Networks: A Survey M. Rakka M. Fouda Pramod P. Khargonekar Fadi J. Kurdahi MQ 25 11 0 11 Aug 2022
Dive into Big Model Training Qinghua Liu Yuxiang Jiang MoMe AI4CE LRM 21 3 0 25 Jul 2022
MCTensor: A High-Precision Deep Learning Library with Multi-Component Floating-Point Tao Yu Wen-Ping Guo Jianan Canal Li Tiancheng Yuan Chris De Sa 27 4 0 18 Jul 2022
GACT: Activation Compressed Training for Generic Network Architectures Xiaoxuan Liu Lianmin Zheng Dequan Wang Yukuo Cen Weize Chen ... Zhiyuan Liu Jie Tang Joey Gonzalez Michael W. Mahoney Alvin Cheung VLM GNN MQ 19 30 0 22 Jun 2022
Low-Precision Stochastic Gradient Langevin Dynamics Ruqi Zhang A. Wilson Chris De Sa BDL 21 14 0 20 Jun 2022
LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models Gunho Park Baeseong Park Minsub Kim Sungjae Lee Jeonghoon Kim Beomseok Kwon S. Kwon Byeongwook Kim Youngjoo Lee Dongsoo Lee MQ 18 73 0 20 Jun 2022
REx: Data-Free Residual Quantization Error Expansion Edouard Yvinec Arnaud Dapgony Matthieu Cord Kévin Bailly MQ 28 8 0 28 Mar 2022
Confidence Dimension for Deep Learning based on Hoeffding Inequality and Relative Evaluation Runqi Wang Linlin Yang Baochang Zhang Wentao Zhu David Doermann Guodong Guo 21 1 0 17 Mar 2022
Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization Jaehong Yoon Geondo Park Wonyong Jeong Sung Ju Hwang FedML 24 19 0 23 Feb 2022
Neural-PIM: Efficient Processing-In-Memory with Neural Approximation of Peripherals Weidong Cao Yilong Zhao Adith Boloor Yinhe Han Xuan Zhang Li Jiang 29 17 0 30 Jan 2022
PocketNN: Integer-only Training and Inference of Neural Networks via Direct Feedback Alignment and Pocket Activations in Pure C++ Jae-Su Song Fangzhen Lin MQ 7 7 0 08 Jan 2022
Which Student is Best? A Comprehensive Knowledge Distillation Exam for Task-Specific BERT Models Made Nindyatama Nityasya Haryo Akbarianto Wibowo Rendi Chevi Radityo Eko Prasojo Alham Fikri Aji 18 4 0 03 Jan 2022
Finding the Task-Optimal Low-Bit Sub-Distribution in Deep Neural Networks Runpei Dong Zhanhong Tan Mengdi Wu Linfeng Zhang Kaisheng Ma MQ 35 11 0 30 Dec 2021
Resource-Efficient Deep Learning: A Survey on Model-, Arithmetic-, and Implementation-Level Techniques JunKyu Lee L. Mukhanov A. S. Molahosseini U. Minhas Yang Hua Jesus Martinez del Rincon K. Dichev Cheol-Ho Hong Hans Vandierendonck 41 29 0 30 Dec 2021
Training Quantized Deep Neural Networks via Cooperative Coevolution Fu Peng Shengcai Liu Ning Lu Ke Tang MQ 26 1 0 23 Dec 2021
Elastic-Link for Binarized Neural Network Jie Hu Ziheng Wu Vince Tan Zhilin Lu Mengze Zeng Enhua Wu MQ 30 6 0 19 Dec 2021
Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization Cheng-Chou Lan MQ 22 0 0 13 Nov 2021
A Survey on Green Deep Learning Jingjing Xu Wangchunshu Zhou Zhiyi Fu Hao Zhou Lei Li VLM 73 83 0 08 Nov 2021