Caiwen Ding

发表

CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-Circulant Weight Matrices

Chao Wang, Yu Bai, Qinru Qiu, 2017, 2017 50th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing

Qinru Qiu, Yanzhi Wang, Bo Yuan, 2016, ASPLOS.

An Automatic and Efficient BERT Pruning for Edge AI Systems

Caiwen Ding, Hongjia Li, N. Liu, 2022, 2022 23rd International Symposium on Quality Electronic Design (ISQED).

Towards Sparsification of Graph Neural Networks

O. Khan, Tong Geng, Caiwen Ding, 2022, 2209.04766.

Towards Sparsification of Graph Neural Networks

O. Khan, Tong Geng, Caiwen Ding, 2022, 2209.04766.

A Multi-Agent Reinforcement Learning Approach for Safe and Efficient Behavior Planning of Connected Autonomous Vehicles

Caiwen Ding, Jie Fu, Songyang Han, 2020, IEEE Transactions on Intelligent Transportation Systems.

Combining multi-view ensemble and surrogate lagrangian relaxation for real-time 3D biomedical image segmentation on the edge

Mikhail A. Bragin, Caiwen Ding, Xiaowei Xu, 2022, Neurocomputing.

PolyMPCNet: Towards ReLU-free Neural Architecture Search in Two-party Computation Based Private Inference

Tong Geng, Caiwen Ding, Wujie Wen, 2022, ArXiv.

Towards Real-Time Temporal Graph Learning

O. Khan, Tong Geng, Caiwen Ding, 2022, 2022 IEEE 40th International Conference on Computer Design (ICCD).

DefectTrack: a deep learning-based multi-object tracking algorithm for quantitative defect analysis of in-situ TEM videos in real-time

Yuanyuan Zhu, Caiwen Ding, Qian Yang, 2022, Scientific Reports.

Securing the Spike: On the Transferabilty and Security of Spiking Neural Networks to Adversarial Examples

Caiwen Ding, Wujie Wen, Nuo Xu, 2022, 2209.03358.

A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining

J. Bi, Tong Geng, Caiwen Ding, 2022, DAC.

Efficient Traffic State Forecasting using Spatio-Temporal Network Dependencies: A Sparse Graph Neural Network Approach

Caiwen Ding, Shaoyi Huang, Monika Filipovska, 2022, ArXiv.

Uncertainty Quantification of Collaborative Detection for Self-Driving

Caiwen Ding, Chen Feng, Songyang Han, 2022, 2209.08162.

You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model

Sheng Tang, Caiwen Ding, Zhenglun Kong, 2022, ArXiv.

Reliability Improvement in RRAM-based DNN for Edge Computing

Saleh Ahmad Khan, Caiwen Ding, Yanzhi Wang, 2022, 2022 IEEE International Symposium on Circuits and Systems (ISCAS).

On the Design of Quantum Graph Convolutional Neural Network in the NISQ-Era and Beyond

O. Khan, Tong Geng, Caiwen Ding, 2022, 2022 IEEE 40th International Conference on Computer Design (ICCD).

TAG: Gradient Attack on Transformer-based Language Models

Hang Liu, Sanguthevar Rajasekaran, Caiwen Ding, 2021, EMNLP.

A Secure and Efficient Federated Learning Framework for NLP

Sanguthevar Rajasekaran, Sheng Lin, Xianrui Meng, 2022, EMNLP.

Variance of the Gradient Also Matters: Privacy Leakage from Gradients

S. Rajasekaran, Caiwen Ding, Binghui Wang, 2022, 2022 International Joint Conference on Neural Networks (IJCNN).

Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning

Marten van Dijk, Caiwen Ding, Sohaib Ahmad, 2022, 2211.14669.

Securing the Spike: On the Transferabilty and Security of Spiking Neural Networks to Adversarial Examples

Caiwen Ding, Wujie Wen, Nuo Xu, 2022, ArXiv.

CoDG-ReRAM: An Algorithm-Hardware Co-design to Accelerate Semi-Structured GNNs on ReRAM

Alexey Tumanov, O. Khan, Tong Geng, 2022, 2022 IEEE 40th International Conference on Computer Design (ICCD).

QuClassi: A Hybrid Deep Neural Network Architecture based on Quantum State Fidelity

Ang Li, Daniel Chen, Betis Baheri, 2021, MLSys.

Dr. Top-k: Delegate-Centric Top-k on GPUs

Hang Liu, Lingda Li, Anil Gaihre, 2021, SC21: International Conference for High Performance Computing, Networking, Storage and Analysis.

Accelerating Dataset Distillation via Model Augmentation

Lei Zhang, J Zhang, Y. Li, 2022, ArXiv.

Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off

Caiwen Ding, Hongwu Peng, Yue Sun, 2022, arXiv.org.

RRNet: Towards ReLU-Reduced Neural Network for Two-party Computation Based Private Inference

Tong Geng, Caiwen Ding, Wujie Wen, 2023, ArXiv.

Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm

I. E. Yen, Caiwen Ding, Dongkuan Xu, 2021, ACL.

E.T.: Re-Thinking Self-Attention for Transformer Models on GPUs

G. Gao, Caiwen Ding, Shaoyi Huang, 2021, SC21: International Conference for High Performance Computing, Networking, Storage and Analysis.

Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning

Hang Liu, Caiwen Ding, Hongwu Peng, 2021, 2021 22nd International Symposium on Quality Electronic Design (ISQED).

Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework pdf

Qinru Qiu, Yanzhi Wang, Xuehai Qian, 2018, AAAI.

VIBNN: Hardware Acceleration of Bayesian Neural Networks

Massoud Pedram, Yanzhi Wang, Xuehai Qian, 2018, ASPLOS.

A SOT-MRAM-based Processing-In-Memory Engine for Highly Compressed DNN Implementation pdf

Caiwen Ding, Sheng Lin, Xiaolong Ma, 2019, ArXiv.

A Majority Logic Synthesis Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits

Yanzhi Wang, Nobuyuki Yoshikawa, Ning Liu, 2019, ACM Great Lakes Symposium on VLSI.

Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs: (Invited Paper)

Jinjun Xiong, Yiyu Shi, Shanglin Zhou, 2021, 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD).

Towards acceleration of deep convolutional neural networks using stochastic computing

Ji Li, Qinru Qiu, Yanzhi Wang, 2017, 2017 22nd Asia and South Pacific Design Automation Conference (ASP-DAC).

ESMFL: Efficient and Secure Models for Federated Learning pdf

Yanzhi Wang, Caiwen Ding, Sheng Lin, 2020, ArXiv.

Hardware-driven nonlinear activation for stochastic computing based deep convolutional neural networks

Ji Li, Qinru Qiu, Yanzhi Wang, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

FTDL: A Tailored FPGA-Overlay for Deep Learning with High Scalability

Hang Liu, He Li, Hayden Kwok-Hay So, 2020, 2020 57th ACM/IEEE Design Automation Conference (DAC).

C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs

Qinru Qiu, Yanzhi Wang, Bo Yuan, 2018, FPGA.

Against Membership Inference Attack: Pruning is All You Need

Hang Liu, Sanguthevar Rajasekaran, Jinbo Bi, 2020, IJCAI.

An Exploratory Approach to Deriving Nutrition Information of Restaurant Food from Crowdsourced Food Images: Case of Hartford

Caiwen Ding, Xiang Chen, R. Xu, 2021, Nutrients.

Uncertainty Quantification of Collaborative Detection for Self-Driving

Caiwen Ding, Chen Feng, Songyang Han, 2022, 2023 IEEE International Conference on Robotics and Automation (ICRA).

REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs

Yun Liang, Yanzhi Wang, Ning Liu, 2019, FPGA.

Collaborative Multi-Object Tracking with Conformal Uncertainty Propagation

Caiwen Ding, Songyang Han, Sanbao Su, 2023, ArXiv.

Accelerating Dataset Distillation via Model Augmentation

Lei Zhang, J Zhang, Y. Li, 2022, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Design, Sensing, and Control of a Novel UAV Platform for Aerial Drilling and Screwing

Lu Lu, Caiwen Ding, Caiwu Ding, 2021, IEEE Robotics and Automation Letters.

Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification

S. Rajasekaran, Caiwen Ding, Nuo Xu, 2022, 2022 IEEE International Conference on Big Data (Big Data).

FTRANS: energy-efficient acceleration of transformers using FPGA

Ji Li, Jieyang Chen, Caiwen Ding, 2020, ISLPED.

FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator

Hang Liu, Xuehai Qian, Xiaolong Ma, 2021, 2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture (ISCA).

You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model

Sheng Tang, Caiwen Ding, Zhenglun Kong, 2022, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

FFT-based deep learning deployment in embedded systems

Massoud Pedram, Hongjia Li, Yanzhi Wang, 2017, 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE).

E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs

Wenyao Xu, Qinru Qiu, Chang Liu, 2018, 2019 IEEE International Symposium on High Performance Computer Architecture (HPCA).

Physics-aware Roughness Optimization for Diffractive Optical Neural Networks

Caiwen Ding, Minhan Lou, Weilu Gao, 2023, arXiv.org.

EVE: Environmental Adaptive Neural Network Models for Low-power Energy Harvesting System

Caiwen Ding, Yufang Jin, Sahidul Islam, 2022, 2022 IEEE/ACM International Conference On Computer Aided Design (ICCAD).

A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods

Xiaolong Ma, Yanzhi Wang, Zheng Zhan, 2021, 2021 58th ACM/IEEE Design Automation Conference (DAC).

Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices

Caiwen Ding, Sahidul Islam, Mimi Xie, 2021, 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE).

Binary Complex Neural Network Acceleration on FPGA : (Invited Paper) pdf

Hang Liu, Hongwu Peng, Mimi Xie, 2021, 2021 IEEE 32nd International Conference on Application-specific Systems, Architectures and Processors (ASAP).

An End-to-end Multi-task Object Detection using Embedded GPU in Autonomous Driving

Caiwen Ding, Shanglin Zhou, Mimi Xie, 2021, 2021 22nd International Symposium on Quality Electronic Design (ISQED).

Enabling Retrain-free Deep Neural Network Pruning Using Surrogate Lagrangian Relaxation

Mikhail A. Bragin, Deniz Gurevin, Lynn Pepin, 2021, IJCAI.

HEIF: Highly Efficient Stochastic Computing-Based Inference Framework for Deep Neural Networks

Ji Li, Qinru Qiu, Yanzhi Wang, 2019, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

Towards Sparsification of Graph Neural Networks

O. Khan, Tong Geng, Caiwen Ding, 2022, 2022 IEEE 40th International Conference on Computer Design (ICCD).

A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework

Yifan Gong, Yanzhi Wang, Wei Niu, 2020, ACM Great Lakes Symposium on VLSI.

PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment

Tong Geng, Caiwen Ding, Wujie Wen, 2023, 2023 60th ACM/IEEE Design Automation Conference (DAC).

Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration

Caiwen Ding, Wujie Wen, Nuo Xu, 2023, 2023 60th ACM/IEEE Design Automation Conference (DAC).

Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off

Caiwen Ding, Hongwu Peng, Yue Sun, 2022, 2023 60th ACM/IEEE Design Automation Conference (DAC).

Aerial Manipulation Using a Novel Unmanned Aerial Vehicle Cyber-Physical System

Caiwen Ding, Hongwu Peng, Caiwu Ding, 2022, ArXiv.

PolyMPCNet: Towards ReLU-free Neural Architecture Search in Two-party Computation Based Private Inference

Tong Geng, Caiwen Ding, Wujie Wen, 2022, ArXiv.

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper)

Hang Liu, Jinbo Bi, Hongwu Peng, 2021, 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD).

HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU

Caiwen Ding, Geng Yuan, Hongwu Peng, 2021, ACM Great Lakes Symposium on VLSI.

Co-Exploration of Graph Neural Network and Network-on-Chip Design Using AutoML

Caiwen Ding, Lei Yang, Shaoyi Huang, 2021, ACM Great Lakes Symposium on VLSI.

Dynamic Gradient Balancing for Enhanced Adversarial Attacks on Multi-Task Models

Caiwen Ding, Hui Guan, Lijun Zhang, 2023, arXiv.org.

Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning

Marten van Dijk, Caiwen Ding, Sohaib Ahmad, 2022, ArXiv.

G AME T HEORETIC M IXED E XPERTS FOR C OMBINA - TIONAL A DVERSARIAL M ACHINE L EARNING

Caiwen Ding, Sohaib Ahmad, Kaleel Mahmood, 2022 .

Dynamic Reconfiguration of Thermoelectric Generators for Vehicle Radiators Energy Harvesting Under Location-Dependent Temperature Variations

Naehyuck Chang, Donghwa Shin, Jaemin Kim, 2018, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

Dancing along Battery: Enabling Transformer with Run-time Reconfigurability on Mobile Devices

Yiyu Shi, Edwin Hsing-Mean Sha, Qingfeng Zhuge, 2021, 2021 58th ACM/IEEE Design Automation Conference (DAC).

Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation

Yanzhi Wang, Xiaolong Ma, Wujie Wen, 2019, 2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC).

FL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery: Special Session Paper

Tong Geng, Caiwen Ding, Ang Li, 2021, 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD).

A Compression-Compilation Framework for On-mobile Real-time BERT Applications

Pu Zhao, Sijia Liu, Caiwen Ding, 2021, IJCAI.

TinyADC: Peripheral Circuit-aware Weight Pruning Framework for Mixed-signal DNN Accelerators

Xiaolong Ma, Mahdi Nazm Bojnordi, Payman Behnam, 2021, 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE).

Graph-Based Shape Analysis for Heterogeneous Geometric Datasets: Similarity, Retrieval and Substructure Matching

Horea T. Ilies, Caiwen Ding, Jiangce Chen, 2021, Comput. Aided Des..

Mapping Transformation Enabled High-Performance and Low-Energy Memristor-Based DNNs

Saleh Ahmad Khan, Yanzhi Wang, Caiwen Ding, 2022, Journal of Low Power Electronics and Applications.

Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning

Ji Li, Caiwen Ding, Tianyun Zhang, 2020, FINDINGS.

Shared Information-Based Safe And Efficient Behavior Planning For Connected Autonomous Vehicles

Caiwen Ding, Songyang Han, Shangli Zhou, 2023, ArXiv.

Memristor crossbar-based ultra-efficient next-generation baseband processors

Bo Yuan, Xiaolong Ma, Caiwen Ding, 2017, 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS).

CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-Circulant Weight Matrices

Qinru Qiu, Yanzhi Wang, X. Lin, 2017, 2017 50th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

An Efficient Deep Reinforcement Learning Framework for UAVs

Lu Lu, Caiwen Ding, Shanglin Zhou, 2020, 2020 21st International Symposium on Quality Electronic Design (ISQED).

Trust: Triangle Counting Reloaded on GPUs

Hang Liu, Adolfy Hoisie, Chen Tian, 2021, IEEE Transactions on Parallel and Distributed Systems.

Towards Lossless Head Pruning through Automatic Peer Distillation for Language Models

Mikhail A. Bragin, Caiwen Ding, Zigeng Wang, 2023, International Joint Conference on Artificial Intelligence.

AutoReP: Automatic ReLU Replacement for Fast Private Network Inference

Caiwen Ding, Wujie Wen, Hongwu Peng, 2023, ArXiv.

SpENCNN: Orchestrating Encoding and Sparsity for Fast Homomorphically Encrypted Neural Network Inference

Wei Wang, Caiwen Ding, Wujie Wen, 2023, ICML.

A Fast and Effective Memristor-Based Method for Finding Approximate Eigenvalues and Eigenvectors of Non-negative Matrices

Yanzhi Wang, Sucheta Soundarajan, Caiwen Ding, 2018, 2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI).

Prediction-based fast thermoelectric generator reconfiguration for energy harvesting from vehicle radiators

Ji Li, Shahin Nazarian, Naehyuck Chang, 2018, 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE).

Tango: rethinking quantization for graph neural network training on GPUs

Da Zheng, Caiwen Ding, Yuede Ji, 2023, arXiv.org.

An Ultra-Efficient Memristor-Based DNN Framework with Structured Weight Pruning and Quantization Using ADMM

Yanzhi Wang, Xiaolong Ma, Sucheta Soundarajan, 2019, 2019 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED).

Detecting Gender Bias in Transformer-based Models: A Case Study on BERT pdf

Hang Liu, Hongwu Peng, Rajat Sainju, 2021, ArXiv.

DeeDiff: Dynamic Uncertainty-Aware Early Exiting for Accelerating Diffusion Model Generation

Y. Li, Caiwen Ding, Yaqing Wang, 2023, ArXiv.

Dynamic Sparse Training via More Exploration

Caiwen Ding, Hongwu Peng, Yue Sun, 2022 .

LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference

Caiwen Ding, Hongwu Peng, Ran Ran, 2023, ArXiv.

Poster: Cryptographic Inferences for Video Deep Neural Networks

Rujia Wang, Caiwen Ding, Yuan Hong, 2022, CCS.

Deep Compressed Pneumonia Detection for Low-Power Embedded Devices pdf

Hongjia Li, Yanzhi Wang, Caiwen Ding, 2019, LABELS/HAL-MICCAI/CuRIOUS@MICCAI.

Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks

O. Khan, Tong Geng, Caiwen Ding, 2023, 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD).

AutoReP: Automatic ReLU Replacement for Fast Private Network Inference

Caiwen Ding, Wujie Wen, Hongwu Peng, 2023, ArXiv.

MergePath-SpMM: Parallel Sparse Matrix-Matrix Algorithm for Graph Neural Network Acceleration

O. Khan, Caiwen Ding, Deniz Gurevin, 2023, 2023 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS).

All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management

Caiwen Ding, Minghai Qin, Pu Zhao, 2022, 2022 IEEE/ACM International Conference On Computer Aided Design (ICCAD).

Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm

I. E. Yen, Caiwen Ding, Dongkuan Xu, 2021, ACL.

Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought

C. Liao, Caiwen Ding, Pei-Hung Lin, 2023, ArXiv.