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2020 – today
- 2024
[j12]Sanbao Su
, Songyang Han, Yiming Li, Zhili Zhang, Chen Feng, Caiwen Ding, Fei Miao:
Collaborative Multi-Object Tracking With Conformal Uncertainty Propagation. IEEE Robotics Autom. Lett. 9(4): 3323-3330 (2024)- [j11]Songyang Han, Shanglin Zhou, Jiangwei Wang, Lynn Pepin, Caiwen Ding, Jie Fu, Fei Miao:
A Multi-Agent Reinforcement Learning Approach for Safe and Efficient Behavior Planning of Connected Autonomous Vehicles. IEEE Trans. Intell. Transp. Syst. 25(5): 3654-3670 (2024) - [c101]Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding:
MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training. ASPLOS (2) 2024: 683-698 - [c100]Yanyue Xie, Peiyan Dong, Geng Yuan, Zhengang Li, Masoud Zabihi, Chao Wu, Sung-En Chang, Xufeng Zhang, Xue Lin, Caiwen Ding, Nobuyuki Yoshikawa, Olivia Chen, Yanzhi Wang:
SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum- Flux - Parametron Superconducting Circuits. DATE 2024: 1-6 - [c99]Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu:
AdaDiff: Accelerating Diffusion Models Through Step-Wise Adaptive Computation. ECCV (79) 2024: 73-90 - [c98]Deniz Gurevin, Mohsin Shan, Shaoyi Huang, Md Amit Hasan, Caiwen Ding, Omer Khan:
PruneGNN: Algorithm-Architecture Pruning Framework for Graph Neural Network Acceleration. HPCA 2024: 108-123 - [c97]Zhengang Li, Alec Lu, Yanyue Xie, Zhenglun Kong, Mengshu Sun, Hao Tang, Zhong Jia Xue, Peiyan Dong, Caiwen Ding, Yanzhi Wang, Xue Lin, Zhenman Fang:
Quasar-ViT: Hardware-Oriented Quantization-Aware Architecture Search for Vision Transformers. ICS 2024: 324-337 - [c96]Hongwu Peng, Caiwen Ding, Tong Geng, Sutanay Choudhury, Kevin J. Barker, Ang Li:
Evaluating Emerging AI/ML Accelerators: IPU, RDU, and NVIDIA/AMD GPUs. ICPE (Companion) 2024: 14-20 - [d2]Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding:
ASPLOS 2024 Artifact for "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training". Version 1. Zenodo, 2024 [all versions]
- [d1]Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding:
ASPLOS 2024 Artifact for "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training". Version 2. Zenodo, 2024 [all versions] - [i84]Bin Lei, Le Chen, Caiwen Ding:
FlashVideo: A Framework for Swift Inference in Text-to-Video Generation. CoRR abs/2401.00869 (2024) - [i83]Bingbing Li, Geng Yuan, Zigeng Wang, Shaoyi Huang, Hongwu Peng, Payman Behnam, Wujie Wen, Hang Liu, Caiwen Ding:
Zero-Space Cost Fault Tolerance for Transformer-based Language Models on ReRAM. CoRR abs/2401.11664 (2024) - [i82]Jiahui Zhao, Ziyi Meng, Stepan Gordeev, Zijie Pan, Dongjin Song, Sandro Steinbach, Caiwen Ding:
Key Information Retrieval to Classify the Unstructured Data Content of Preferential Trade Agreements. CoRR abs/2401.12520 (2024) - [i81]Binghao Lu, Caiwen Ding, Jinbo Bi, Dongjin Song:
Weakly Supervised Change Detection via Knowledge Distillation and Multiscale Sigmoid Inference. CoRR abs/2403.05796 (2024) - [i80]Shijin Duan, Chenghong Wang, Hongwu Peng, Yukui Luo, Wujie Wen, Caiwen Ding, Xiaolin Xu:
SSNet: A Lightweight Multi-Party Computation Scheme for Practical Privacy-Preserving Machine Learning Service in the Cloud. CoRR abs/2406.02629 (2024) - [i79]Tong Zhou, Jiahui Zhao, Yukui Luo, Xi Xie, Wujie Wen, Caiwen Ding, Xiaolin Xu:
AdaPI: Facilitating DNN Model Adaptivity for Efficient Private Inference in Edge Computing. CoRR abs/2407.05633 (2024) - [i78]Zijie Pan, Stepan Gordeev, Jiahui Zhao, Ziyi Meng, Caiwen Ding, Sandro Steinbach, Dongjin Song:
International Trade Flow Prediction with Bilateral Trade Provisions. CoRR abs/2407.13698 (2024) - [i77]Zhengang Li, Alec Lu, Yanyue Xie, Zhenglun Kong, Mengshu Sun, Hao Tang, Zhong Jia Xue, Peiyan Dong, Caiwen Ding, Yanzhi Wang, Xue Lin, Zhenman Fang:
Quasar-ViT: Hardware-Oriented Quantization-Aware Architecture Search for Vision Transformers. CoRR abs/2407.18175 (2024) - [i76]Yanyue Xie, Peiyan Dong, Geng Yuan, Zhengang Li, Masoud Zabihi, Chao Wu, Sung-En Chang, Xufeng Zhang, Xue Lin, Caiwen Ding, Nobuyuki Yoshikawa, Olivia Chen, Yanzhi Wang:
SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum-Flux-Parametron Superconducting Circuits. CoRR abs/2407.18209 (2024) - 2023
- [j10]Zeinab S. Jalali, Chenghong Wang, Griffin Kearney, Geng Yuan, Caiwen Ding, Yinan Zhou, Yanzhi Wang, Sucheta Soundarajan:
Memristor-Based Spectral Decomposition of Matrices and Its Applications. IEEE Trans. Computers 72(5): 1460-1472 (2023) - [j9]Shanglin Zhou, Mikhail A. Bragin, Deniz Gurevin, Lynn Pepin, Fei Miao, Caiwen Ding:
Surrogate Lagrangian Relaxation: A Path to Retrain-Free Deep Neural Network Pruning. ACM Trans. Design Autom. Electr. Syst. 28(6): 102:1-102:19 (2023) - [c95]Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu:
You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model. CVPR 2023: 10781-10791 - [c94]Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu:
Accelerating Dataset Distillation via Model Augmentation. CVPR 2023: 11950-11959 - [c93]Yifan Gong, Pu Zhao, Zheng Zhan, Yushu Wu, Chao Wu, Zhenglun Kong, Minghai Qin, Caiwen Ding, Yanzhi Wang:
Condense: A Framework for Device and Frequency Adaptive Neural Network Models on the Edge. DAC 2023: 1-6 - [c92]Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding:
Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration. DAC 2023: 1-6 - [c91]Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding:
Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off. DAC 2023: 1-6 - [c90]Zhuo Liu, Yunan Yang, Zhenyu Pan, Anshujit Sharma, Amit Hasan, Caiwen Ding, Ang Li, Michael C. Huang, Tong Geng:
Ising-CF: A Pathbreaking Collaborative Filtering Method Through Efficient Ising Machine Learning. DAC 2023: 1-6 - [c89]Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding:
PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment. DAC 2023: 1-6 - [c88]Shanglin Zhou, Yingjie Li, Minhan Lou, Weilu Gao, Zhijie Shi, Cunxi Yu, Caiwen Ding:
Physics-aware Roughness Optimization for Diffractive Optical Neural Networks. DAC 2023: 1-6 - [c87]Andy Trinh, Shivam Sheth, Anil Gaihre, Caiwen Ding, Jieyang Chen, Feiyi Wang, David Pugmire, Scott Klasky, Hang Liu, Lipeng Wan:
Understanding Node Allocation on Leadership-Class Supercomputers with Graph Analytics. HPCC/DSS/SmartCity/DependSys 2023: 780-787 - [c86]Bin Lei, Caiwen Ding, Le Chen, Pei-Hung Lin, Chunhua Liao:
Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C++. HPEC 2023: 1-7 - [c85]Xi Xie, Hongwu Peng, Amit Hasan, Shaoyi Huang, Jiahui Zhao, Haowen Fang, Wei Zhang, Tong Geng, Omer Khan, Caiwen Ding:
Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks. ICCAD 2023: 1-9 - [c84]Hongwu Peng, Shaoyi Huang, Tong Zhou, Yukui Luo, Chenghong Wang, Zigeng Wang, Jiahui Zhao, Xi Xie, Ang Li, Tony Geng, Kaleel Mahmood, Wujie Wen, Xiaolin Xu, Caiwen Ding:
AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. ICCV 2023: 5155-5165 - [c83]Ran Ran, Xinwei Luo, Wei Wang, Tao Liu, Gang Quan, Xiaolin Xu, Caiwen Ding, Wujie Wen:
SpENCNN: Orchestrating Encoding and Sparsity for Fast Homomorphically Encrypted Neural Network Inference. ICML 2023: 28718-28728 - [c82]Sanbao Su, Yiming Li, Sihong He, Songyang Han, Chen Feng, Caiwen Ding, Fei Miao:
Uncertainty Quantification of Collaborative Detection for Self-Driving. ICRA 2023: 5588-5594 - [c81]Bingbing Li, Zigeng Wang, Shaoyi Huang, Mikhail A. Bragin, Ji Li, Caiwen Ding:
Towards Lossless Head Pruning through Automatic Peer Distillation for Language Models. IJCAI 2023: 5113-5121 - [c80]Mohsin Shan, Deniz Gurevin, Jared Nye, Caiwen Ding, Omer Khan:
MergePath-SpMM: Parallel Sparse Matrix-Matrix Algorithm for Graph Neural Network Acceleration. ISPASS 2023: 145-156 - [c79]Ya-sine Agrignan, Shanglin Zhou, Jun Bai, Sahidul Islam, Sheida Nabavi, Mimi Xie, Caiwen Ding:
A Deep Learning Approach for Ventricular Arrhythmias Classification using Microcontroller. ISQED 2023: 1-5 - [c78]Zigeng Wang, Bingbing Li, Xia Xiao, Tianyun Zhang, Mikhail A. Bragin, Bing Yan, Caiwen Ding, Sanguthevar Rajasekaran:
Automatic Subnetwork Search Through Dynamic Differentiable Neuron Pruning. ISQED 2023: 1-6 - [c77]Yukui Luo, Nuo Xu, Hongwu Peng, Chenghong Wang, Shijin Duan, Kaleel Mahmood, Wujie Wen, Caiwen Ding, Xiaolin Xu:
AQ2PNN: Enabling Two-party Privacy-Preserving Deep Neural Network Inference with Adaptive Quantization. MICRO 2023: 628-640 - [c76]Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding:
LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference. NeurIPS 2023 - [c75]Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu:
TANGO: re-thinking quantization for graph neural network training on GPUs. SC 2023: 38:1-38:14 - [c74]Ce Feng, Nuo Xu, Wujie Wen, Parv Venkitasubramaniam, Caiwen Ding:
Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering. SP 2023: 1944-1960 - [i75]Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Shaoyi Huang, Xi Xie, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding:
RRNet: Towards ReLU-Reduced Neural Network for Two-party Computation Based Private Inference. CoRR abs/2302.02292 (2023) - [i74]Songyang Han, Shanglin Zhou, Lynn Pepin, Jiangwei Wang, Caiwen Ding, Fei Miao:
Shared Information-Based Safe And Efficient Behavior Planning For Connected Autonomous Vehicles. CoRR abs/2302.04321 (2023) - [i73]Sanbao Su, Songyang Han, Yiming Li, Zhili Zhang, Chen Feng, Caiwen Ding, Fei Miao:
Collaborative Multi-Object Tracking with Conformal Uncertainty Propagation. CoRR abs/2303.14346 (2023) - [i72]Shanglin Zhou, Yingjie Li, Minhan Lou, Weilu Gao, Zhijie Shi, Cunxi Yu, Caiwen Ding:
Physics-aware Roughness Optimization for Diffractive Optical Neural Networks. CoRR abs/2304.01500 (2023) - [i71]Shanglin Zhou, Mikhail A. Bragin, Lynn Pepin, Deniz Gurevin, Fei Miao, Caiwen Ding:
Surrogate Lagrangian Relaxation: A Path To Retrain-free Deep Neural Network Pruning. CoRR abs/2304.04120 (2023) - [i70]Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding:
Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration. CoRR abs/2304.12214 (2023) - [i69]Lijun Zhang, Xiao Liu, Kaleel Mahmood, Caiwen Ding, Hui Guan:
Dynamic Gradient Balancing for Enhanced Adversarial Attacks on Multi-Task Models. CoRR abs/2305.12066 (2023) - [i68]Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding:
PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment. CoRR abs/2306.15513 (2023) - [i67]Bin Lei, Caiwen Ding, Le Chen, Pei-Hung Lin, Chunhua Liao:
Creating a Dataset for High-Performance Computing Code Translation: A Bridge Between HPC Fortran and C++. CoRR abs/2307.07686 (2023) - [i66]Ce Feng, Nuo Xu, Wujie Wen, Parv Venkitasubramaniam, Caiwen Ding:
Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering. CoRR abs/2307.13231 (2023) - [i65]Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu:
Tango: rethinking quantization for graph neural network training on GPUs. CoRR abs/2308.00890 (2023) - [i64]Bin Lei, Pei-Hung Lin, Chunhua Liao, Caiwen Ding:
Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought. CoRR abs/2308.08614 (2023) - [i63]Bin Lei, Sheng Lin, Pei-Hung Lin, Chunhua Liao, Caiwen Ding:
Towards Zero Memory Footprint Spiking Neural Network Training. CoRR abs/2308.08649 (2023) - [i62]Hongwu Peng, Shaoyi Huang, Tong Zhou, Yukui Luo, Chenghong Wang, Zigeng Wang, Jiahui Zhao, Xi Xie, Ang Li, Tony Geng, Kaleel Mahmood, Wujie Wen, Xiaolin Xu, Caiwen Ding:
AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. CoRR abs/2308.10134 (2023) - [i61]Xi Xie, Hongwu Peng, Amit Hasan, Shaoyi Huang, Jiahui Zhao, Haowen Fang, Wei Zhang, Tong Geng, Omer Khan, Caiwen Ding:
Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks. CoRR abs/2308.11825 (2023) - [i60]Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding:
LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference. CoRR abs/2309.14331 (2023) - [i59]Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu:
DeeDiff: Dynamic Uncertainty-Aware Early Exiting for Accelerating Diffusion Model Generation. CoRR abs/2309.17074 (2023) - [i58]Hongwu Peng, Caiwen Ding, Tong Geng, Sutanay Choudhury, Kevin J. Barker, Ang Li:
Evaluating Emerging AI/ML Accelerators: IPU, RDU, and NVIDIA/AMD GPUs. CoRR abs/2311.04417 (2023) - [i57]Kiran Thorat, Jiahui Zhao, Yaotian Liu, Hongwu Peng, Xi Xie, Bin Lei, Jeff Zhang, Caiwen Ding:
Advanced Large Language Model (LLM)-Driven Verilog Development: Enhancing Power, Performance, and Area Optimization in Code Synthesis. CoRR abs/2312.01022 (2023) - [i56]Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding:
MaxK-GNN: Towards Theoretical Speed Limits for Accelerating Graph Neural Networks Training. CoRR abs/2312.08656 (2023) - 2022
- [j8]Jiangce Chen, Horea T. Ilies, Caiwen Ding:
Graph-Based Shape Analysis for Heterogeneous Geometric Datasets: Similarity, Retrieval and Substructure Matching. Comput. Aided Des. 143: 103125 (2022) - [c73]Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Yijue Wang, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Sanguthevar Rajasekaran, Hang Liu, Caiwen Ding:
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. ACL (1) 2022: 190-200 - [c72]Yijue Wang, Nuo Xu, Shaoyi Huang, Kaleel Mahmood, Dan Guo, Caiwen Ding, Wujie Wen, Sanguthevar Rajasekaran:
Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification. IEEE Big Data 2022: 5823-5832 - [c71]Bingyu Liu, Rujia Wang, Zhongjie Ba, Shanglin Zhou, Caiwen Ding, Yuan Hong:
Poster: Cryptographic Inferences for Video Deep Neural Networks. CCS 2022: 3395-3397 - [c70]Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu, Caiwen Ding:
A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining. DAC 2022: 1135-1140 - [c69]Sahidul Islam, Jieren Deng, Shanglin Zhou, Chen Pan, Caiwen Ding, Mimi Xie:
Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices. DATE 2022: 921-926 - [c68]Sahidul Islam, Shanglin Zhou, Ran Ran, Yufang Jin, Wujie Wen, Caiwen Ding, Mimi Xie:
EVE: Environmental Adaptive Neural Network Models for Low-Power Energy Harvesting System. ICCAD 2022: 35:1-35:9 - [c67]Yifan Gong, Zheng Zhan, Pu Zhao, Yushu Wu, Chao Wu, Caiwen Ding, Weiwen Jiang, Minghai Qin, Yanzhi Wang:
All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management. ICCAD 2022: 133:1-133:9 - [c66]Deniz Gurevin, Mohsin Shan, Tong Geng, Weiwen Jiang, Caiwen Ding, Omer Khan:
Towards Real-Time Temporal Graph Learning. ICCD 2022: 263-271 - [c65]Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding:
Towards Sparsification of Graph Neural Networks. ICCD 2022: 272-279 - [c64]Yixuan Luo, Payman Behnam, Kiran Thorat, Zhuo Liu, Hongwu Peng, Shaoyi Huang, Shu Zhou, Omer Khan, Alexey Tumanov, Caiwen Ding, Tong Geng:
CoDG-ReRAM: An Algorithm-Hardware Co-design to Accelerate Semi-Structured GNNs on ReRAM. ICCD 2022: 280-289 - [c63]Zhirui Hu, Jinyang Li, Zhenyu Pan, Shanglin Zhou, Lei Yang, Caiwen Ding, Omer Khan, Tong Geng, Weiwen Jiang:
On the Design of Quantum Graph Convolutional Neural Network in the NISQ-Era and Beyond. ICCD 2022: 290-297 - [c62]Yijue Wang, Jieren Deng, Dan Guo, Chenghong Wang, Xianrui Meng, Hang Liu, Chao Shang, Binghui Wang, Qin Cao, Caiwen Ding, Sanguthevar Rajasekaran:
Variance of the Gradient Also Matters: Privacy Leakage from Gradients. IJCNN 2022: 1-8 - [c61]Md. Oli-Uz-Zaman, Saleh Ahmad Khan, Geng Yuan, Yanzhi Wang, Zhiheng Liao, Jingyan Fu, Caiwen Ding, Jinhui Wang:
Reliability Improvement in RRAM-based DNN for Edge Computing. ISCAS 2022: 581-585 - [c60]Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding:
An Automatic and Efficient BERT Pruning for Edge AI Systems. ISQED 2022: 1-6 - [c59]Wei Wei, Sahidul Islam, Jishnu Banerjee, Shanglin Zhou, Chen Pan, Caiwen Ding, Mimi Xie:
An Intermittent OTA Approach to Update the DL Weights on Energy Harvesting Devices. ISQED 2022: 1-6 - [c58]Samuel Alexander Stein, Betis Baheri, Daniel Chen, Ying Mao, Qiang Guan, Ang Li, Shuai Xu, Caiwen Ding:
QuClassi: A Hybrid Deep Neural Network Architecture based on Quantum State Fidelity. MLSys 2022 - [i55]Jieren Deng, Chenghong Wang, Xianrui Meng, Yijue Wang, Ji Li, Sheng Lin, Shuo Han, Fei Miao, Sanguthevar Rajasekaran, Caiwen Ding:
A Secure and Efficient Federated Learning Framework for NLP. CoRR abs/2201.11934 (2022) - [i54]Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding:
An Automatic and Efficient BERT Pruning for Edge AI Systems. CoRR abs/2206.10461 (2022) - [i53]Sahidul Islam, Shanglin Zhou, Ran Ran, Yufang Jin, Wujie Wen, Caiwen Ding, Mimi Xie:
EVE: Environmental Adaptive Neural Network Models for Low-power Energy Harvesting System. CoRR abs/2207.09258 (2022) - [i52]Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu, Caiwen Ding:
A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining. CoRR abs/2208.03646 (2022) - [i51]Nuo Xu, Kaleel Mahmood, Haowen Fang, Ethan Rathbun, Caiwen Ding, Wujie Wen:
Securing the Spike: On the Transferabilty and Security of Spiking Neural Networks to Adversarial Examples. CoRR abs/2209.03358 (2022) - [i50]Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding:
Towards Sparsification of Graph Neural Networks. CoRR abs/2209.04766 (2022) - [i49]Sanbao Su, Yiming Li, Sihong He, Songyang Han, Chen Feng, Caiwen Ding, Fei Miao:
Uncertainty Quantification of Collaborative Detection for Self-Driving. CoRR abs/2209.08162 (2022) - [i48]Deniz Gurevin, Mohsin Shan, Tong Geng, Weiwen Jiang, Caiwen Ding, Omer Khan:
Towards Real-Time Temporal Graph Learning. CoRR abs/2210.04114 (2022) - [i47]Caiwu Ding, Hongwu Peng, Lu Lu, Caiwen Ding:
Aerial Manipulation Using a Novel Unmanned Aerial Vehicle Cyber-Physical System. CoRR abs/2210.15632 (2022) - [i46]Bin Lei, Shaoyi Huang, Caiwen Ding, Monika Filipovska:
Efficient Traffic State Forecasting using Spatio-Temporal Network Dependencies: A Sparse Graph Neural Network Approach. CoRR abs/2211.03033 (2022) - [i45]Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu:
You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model. CoRR abs/2211.11152 (2022) - [i44]Ethan Rathbun, Kaleel Mahmood, Sohaib Ahmad, Caiwen Ding, Marten van Dijk:
Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning. CoRR abs/2211.14669 (2022) - [i43]Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding:
Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off. CoRR abs/2211.16667 (2022) - [i42]Yifan Gong, Zheng Zhan, Pu Zhao, Yushu Wu, Chao Wu, Caiwen Ding, Weiwen Jiang, Minghai Qin, Yanzhi Wang:
All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management. CoRR abs/2212.05122 (2022) - [i41]Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu:
Accelerating Dataset Distillation via Model Augmentation. CoRR abs/2212.06152 (2022) - 2021
- [j7]Caiwu Ding, Lu Lu, Cong Wang, Caiwen Ding:
Design, Sensing, and Control of a Novel UAV Platform for Aerial Drilling and Screwing. IEEE Robotics Autom. Lett. 6(2): 3176-3183 (2021) - [j6]Santosh Pandey, Zhibin Wang, Sheng Zhong, Chen Tian, Bolong Zheng, Xiaoye S. Li, Lingda Li, Adolfy Hoisie, Caiwen Ding, Dong Li, Hang Liu:
Trust: Triangle Counting Reloaded on GPUs. IEEE Trans. Parallel Distributed Syst. 32(11): 2646-2660 (2021) - [c57]Hongwu Peng, Shanglin Zhou, Scott Weitze, Jiaxin Li, Sahidul Islam, Tong Geng, Ang Li, Wei Zhang, Minghu Song, Mimi Xie, Hang Liu, Caiwen Ding:
Binary Complex Neural Network Acceleration on FPGA : (Invited Paper). ASAP 2021: 85-92 - [c56]Tianyun Zhang, Xiaolong Ma, Zheng Zhan, Shanglin Zhou, Caiwen Ding, Makan Fardad, Yanzhi Wang:
A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods. DAC 2021: 493-498 - [c55]Yuhong Song, Weiwen Jiang, Bingbing Li, Panjie Qi, Qingfeng Zhuge, Edwin Hsing-Mean Sha, Sakyasingha Dasgupta, Yiyu Shi, Caiwen Ding:
Dancing along Battery: Enabling Transformer with Run-time Reconfigurability on Mobile Devices. DAC 2021: 1003-1008 - [c54]Geng Yuan, Payman Behnam, Yuxuan Cai, Ali Shafiee, Jingyan Fu, Zhiheng Liao, Zhengang Li, Xiaolong Ma, Jieren Deng, Jinhui Wang, Mahdi Nazm Bojnordi, Yanzhi Wang, Caiwen Ding:
TinyADC: Peripheral Circuit-aware Weight Pruning Framework for Mixed-signal DNN Accelerators. DATE 2021: 926-931 - [c53]Jieren Deng, Yijue Wang, Ji Li, Chenghong Wang, Chao Shang, Hang Liu, Sanguthevar Rajasekaran, Caiwen Ding:
TAG: Gradient Attack on Transformer-based Language Models. EMNLP (Findings) 2021: 3600-3610 - [c52]Chenghong Wang, Jieren Deng, Xianrui Meng, Yijue Wang, Ji Li, Sheng Lin, Shuo Han, Fei Miao, Sanguthevar Rajasekaran, Caiwen Ding:
A Secure and Efficient Federated Learning Framework for NLP. EMNLP (1) 2021: 7676-7682 - [c51]Shaoyi Huang, Shiyang Chen, Hongwu Peng, Daniel Manu, Zhenglun Kong, Geng Yuan, Lei Yang, Shusen Wang, Hang Liu, Caiwen Ding:
HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU. ACM Great Lakes Symposium on VLSI 2021: 169-174 - [c50]Daniel Manu, Shaoyi Huang, Caiwen Ding, Lei Yang:
Co-Exploration of Graph Neural Network and Network-on-Chip Design Using AutoML. ACM Great Lakes Symposium on VLSI 2021: 175-180 - [c49]Daniel Manu, Yi Sheng, Junhuan Yang, Jieren Deng, Tong Geng, Ang Li, Caiwen Ding, Weiwen Jiang, Lei Yang:
FL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery: Special Session Paper. ICCAD 2021: 1-7 - [c48]Hongwu Peng, Shiyang Chen, Zhepeng Wang, Junhuan Yang, Scott A. Weitze, Tong Geng, Ang Li, Jinbo Bi, Minghu Song, Weiwen Jiang,