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2020 – today
- 2022
[j9]Yongan Zhang, Anton Banta, Yonggan Fu, Mathews M. John, Allison Post, Mehdi Razavi, Joseph R. Cavallaro, Behnaam Aazhang, Yingyan Lin:
RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms. ACM J. Emerg. Technol. Comput. Syst. 18(2): 29:1-29:25 (2022)- [c46]Haoran You, Zhihan Lu, Zijian Zhou, Yonggan Fu, Yingyan Lin:
Early-Bird GCNs: Graph-Network Co-optimization towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets. AAAI 2022: 8910-8918 - [c45]Zhongzhi Yu, Yonggan Fu, Sicheng Li, Chaojian Li, Yingyan Lin:
MIA-Former: Efficient and Robust Vision Transformers via Multi-Grained Input-Adaptation. AAAI 2022: 8962-8970 - [c44]Anqi Guo, Tong Geng, Yongan Zhang, Pouya Haghi, Chunshu Wu, Cheng Tan, Yingyan Lin, Ang Li, Martin C. Herbordt:
FCsN: A FPGA-Centric SmartNIC Framework for Neural Networks. FCCM 2022: 1-2 - [c43]Haoran You, Tong Geng, Yongan Zhang, Ang Li, Yingyan Lin:
GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design. HPCA 2022: 460-474 - [c42]Yonggan Fu, Haichuan Yang, Jiayi Yuan, Meng Li, Cheng Wan, Raghuraman Krishnamoorthi, Vikas Chandra, Yingyan Lin:
DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks. ICML 2022: 6849-6862 - [c41]Haoran You, Baopu Li, Huihong Shi, Yonggan Fu, Yingyan Lin:
ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks. ICML 2022: 25566-25580 - [c40]Haoran You, Cheng Wan, Yang Zhao, Zhongzhi Yu, Yonggan Fu, Jiayi Yuan, Shang Wu, Shunyao Zhang, Yongan Zhang, Chaojian Li, Vivek Boominathan, Ashok Veeraraghavan, Ziyun Li, Yingyan Lin:
EyeCoD: eye tracking system acceleration via flatcam-based algorithm & accelerator co-design. ISCA 2022: 610-622 - [c39]Cheng Wan, Youjie Li, Ang Li, Nam Sung Kim, Yingyan Lin:
BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling. MLSys 2022 - [c38]Yang Zhao, Ziyun Li, Yonggan Fu, Yongan Zhang, Chaojian Li, Cheng Wan, Haoran You, Shang Wu, Xu Ouyang, Vivek Boominathan, Ashok Veeraraghavan, Yingyan Lin:
i-FlatCam: A 253 FPS, 91.49 µJ/Frame Ultra-Compact Intelligent Lensless Camera for Real-Time and Efficient Eye Tracking in VR/AR. VLSI Technology and Circuits 2022: 108-109 - [c37]Yang Zhao, Yongan Zhang, Yonggan Fu, Xu Ouyang, Cheng Wan, Shang Wu, Anton Banta, Mathews M. John, Allison Post, Mehdi Razavi, Joseph R. Cavallaro, Behnaam Aazhang, Yingyan Lin:
e-G2C: A 0.14-to-8.31 µJ/Inference NN-based Processor with Continuous On-chip Adaptation for Anomaly Detection and ECG Conversion from EGM. VLSI Technology and Circuits 2022: 252-253 - [i43]Tong Geng, Chunshu Wu, Yongan Zhang, Cheng Tan, Chenhao Xie, Haoran You, Martin C. Herbordt, Yingyan Lin, Ang Li:
I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization. CoRR abs/2203.03606 (2022) - [i42]Zhongzhi Yu, Yonggan Fu, Shang Wu, Mengquan Li, Haoran You, Yingyan Lin:
LDP: Learnable Dynamic Precision for Efficient Deep Neural Network Training and Inference. CoRR abs/2203.07713 (2022) - [i41]Yonggan Fu, Shunyao Zhang, Shang Wu, Cheng Wan, Yingyan Lin:
Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations? CoRR abs/2203.08392 (2022) - [i40]Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin:
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication. CoRR abs/2203.10428 (2022) - [i39]Cheng Wan, Youjie Li, Ang Li, Nam Sung Kim, Yingyan Lin:
BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling. CoRR abs/2203.10983 (2022) - [i38]Haoran You, Baopu Li, Huihong Shi, Yonggan Fu, Yingyan Lin:
ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks. CoRR abs/2205.08119 (2022) - [i37]Yonggan Fu, Haichuan Yang, Jiayi Yuan, Meng Li, Cheng Wan, Raghuraman Krishnamoorthi, Vikas Chandra, Yingyan Lin:
DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks. CoRR abs/2206.00843 (2022) - [i36]Haoran You, Cheng Wan, Yang Zhao, Zhongzhi Yu, Yonggan Fu, Jiayi Yuan, Shang Wu, Shunyao Zhang, Yongan Zhang, Chaojian Li, Vivek Boominathan, Ashok Veeraraghavan, Ziyun Li, Yingyan Lin:
EyeCoD: Eye Tracking System Acceleration via FlatCam-based Algorithm & Accelerator Co-Design. CoRR abs/2206.00877 (2022) - [i35]Yang Zhao, Ziyun Li, Yonggan Fu, Yongan Zhang, Chaojian Li, Cheng Wan, Haoran You, Shang Wu, Xu Ouyang, Vivek Boominathan, Ashok Veeraraghavan, Yingyan Lin:
i-FlatCam: A 253 FPS, 91.49 μJ/Frame Ultra-Compact Intelligent Lensless Camera for Real-Time and Efficient Eye Tracking in VR/AR. CoRR abs/2206.08141 (2022) - [i34]Haoran You, Baopu Li, Zhanyi Sun, Xu Ouyang, Yingyan Lin:
SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning. CoRR abs/2207.03677 (2022) - 2021
- [j8]Yiran Chen, Qinru Qiu, Yingyan Lin:
Introduction of Special Issue on Hardware and Algorithms for Efficient Machine Learning-Part 1. ACM J. Emerg. Technol. Comput. Syst. 17(2): 18:1-18:2 (2021) - [j7]Yiran Chen, Qinru Qiu, Yingyan Lin:
Introduction to the Special Issue on Hardware and Algorithms for Efficient Machine Learning - Part 2. ACM J. Emerg. Technol. Comput. Syst. 17(4): 45:1-45:2 (2021) - [j6]Xing Hu
, Yang Zhao, Lei Deng, Ling Liang, Pengfei Zuo, Jing Ye, Yingyan Lin, Yuan Xie:
Practical Attacks on Deep Neural Networks by Memory Trojaning. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 40(6): 1230-1243 (2021) - [j5]Riccardo Petrolo, Zhambyl Shaikhanov, Yingyan Lin, Edward W. Knightly:
ASTRO: A System for Off-grid Networked Drone Sensing Missions. ACM Trans. Internet Things 2(4): 24:1-24:22 (2021) - [j4]Sicong Liu, Junzhao Du, Kaiming Nan, Zimu Zhou, Hui Liu, Zhangyang Wang, Yingyan Lin:
AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles. IEEE Trans. Mob. Comput. 20(12): 3282-3297 (2021) - [c36]Yonggan Fu, Yongan Zhang, Chaojian Li, Zhongzhi Yu, Yingyan Lin:
A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning. DAC 2021: 13-18 - [c35]Yonggan Fu, Zhongzhi Yu, Yongan Zhang, Yifan Jiang, Chaojian Li, Yongyuan Liang, Mingchao Jiang, Zhangyang Wang, Yingyan Lin:
InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks. DAC 2021: 757-762 - [c34]Yiming Qiu, Hongyi Liu, Thomas E. Anderson, Yingyan Lin, Ang Chen:
Toward reconfigurable kernel datapaths with learned optimizations. HotOS 2021: 175-182 - [c33]Mengquan Li, Zhongzhi Yu, Yongan Zhang, Yonggan Fu, Yingyan Lin:
O-HAS: Optical Hardware Accelerator Search for Boosting Both Acceleration Performance and Development Speed. ICCAD 2021: 1-9 - [c32]Yongan Zhang, Haoran You, Yonggan Fu, Tong Geng, Ang Li, Yingyan Lin:
G-CoS: GNN-Accelerator Co-Search Towards Both Better Accuracy and Efficiency. ICCAD 2021: 1-9 - [c31]Yonggan Fu, Yang Zhang, Yue Wang, Zhihan Lu, Vivek Boominathan, Ashok Veeraraghavan, Yingyan Lin:
SACoD: Sensor Algorithm Co-Design Towards Efficient CNN-powered Intelligent PhlatCam. ICCV 2021: 5148-5157 - [c30]Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin:
CPT: Efficient Deep Neural Network Training via Cyclic Precision. ICLR 2021 - [c29]Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Cong Hao, Yingyan Lin:
HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark. ICLR 2021 - [c28]Yonggan Fu, Qixuan Yu, Meng Li, Vikas Chandra, Yingyan Lin:
Double-Win Quant: Aggressively Winning Robustness of Quantized Deep Neural Networks via Random Precision Training and Inference. ICML 2021: 3492-3504 - [c27]Yonggan Fu, Yongan Zhang, Yang Zhang, David D. Cox, Yingyan Lin:
Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators. ICML 2021: 3505-3517 - [c26]Yongan Zhang, Yonggan Fu, Weiwen Jiang, Chaojian Li, Haoran You, Meng Li, Vikas Chandra, Yingyan Lin:
DIAN: Differentiable Accelerator-Network Co-Search Towards Maximal DNN Efficiency. ISLPED 2021: 1-6 - [c25]Yonggan Fu, Yang Zhao, Qixuan Yu, Chaojian Li, Yingyan Lin:
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency. MICRO 2021: 225-237 - [c24]Tong Geng, Chunshu Wu, Yongan Zhang, Cheng Tan, Chenhao Xie, Haoran You, Martin C. Herbordt, Yingyan Lin, Ang Li:
I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization. MICRO 2021: 1051-1063 - [c23]Yonggan Fu, Qixuan Yu, Yang Zhang, Shang Wu, Xu Ouyang, David D. Cox, Yingyan Lin:
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks. NeurIPS 2021: 13059-13072 - [c22]Zhaozhuo Xu, Beidi Chen, Chaojian Li, Weiyang Liu, Le Song, Yingyan Lin, Anshumali Shrivastava:
Locality Sensitive Teaching. NeurIPS 2021: 18049-18062 - [i33]Xiaohan Chen, Yang Zhao, Yue Wang, Pengfei Xu, Haoran You, Chaojian Li, Yonggan Fu, Yingyan Lin, Zhangyang Wang:
SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training. CoRR abs/2101.01163 (2021) - [i32]Randall Balestriero, Haoran You, Zhihan Lu, Yutong Kou, Yingyan Lin, Richard G. Baraniuk:
Max-Affine Spline Insights Into Deep Network Pruning. CoRR abs/2101.02338 (2021) - [i31]Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin:
CPT: Efficient Deep Neural Network Training via Cyclic Precision. CoRR abs/2101.09868 (2021) - [i30]Haoran You, Zhihan Lu, Zijian Zhou, Yingyan Lin:
GEBT: Drawing Early-Bird Tickets in Graph Convolutional Network Training. CoRR abs/2103.00794 (2021) - [i29]Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Yingyan Lin:
HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark. CoRR abs/2103.10584 (2021) - [i28]Yonggan Fu, Zhongzhi Yu, Yongan Zhang, Yifan Jiang, Chaojian Li, Yongyuan Liang, Mingchao Jiang, Zhangyang Wang, Yingyan Lin:
InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks. CoRR abs/2104.10853 (2021) - [i27]Yonggan Fu, Yongan Zhang, Yang Zhang, David D. Cox, Yingyan Lin:
Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators. CoRR abs/2106.06575 (2021) - [i26]Yonggan Fu, Yongan Zhang, Chaojian Li, Zhongzhi Yu, Yingyan Lin:
A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning. CoRR abs/2106.06577 (2021) - [i25]Chaojian Li, Wuyang Chen, Yuchen Gu, Tianlong Chen, Yonggan Fu, Zhangyang Wang, Yingyan Lin:
DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference. CoRR abs/2107.07706 (2021) - [i24]Mengquan Li, Zhongzhi Yu, Yongan Zhang, Yonggan Fu, Yingyan Lin:
O-HAS: Optical Hardware Accelerator Search for Boosting Both Acceleration Performance and Development Speed. CoRR abs/2108.07538 (2021) - [i23]Yonggan Fu, Yang Zhao, Qixuan Yu, Chaojian Li, Yingyan Lin:
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency. CoRR abs/2109.05223 (2021) - [i22]Yongan Zhang, Haoran You, Yonggan Fu, Tong Geng, Ang Li, Yingyan Lin:
G-CoS: GNN-Accelerator Co-Search Towards Both Better Accuracy and Efficiency. CoRR abs/2109.08983 (2021) - [i21]Yonggan Fu, Qixuan Yu, Yang Zhang, Shang Wu, Xu Ouyang, David D. Cox, Yingyan Lin:
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks. CoRR abs/2110.14068 (2021) - [i20]Yongan Zhang, Anton Banta, Yonggan Fu, Mathews M. John, Allison Post, Mehdi Razavi, Joseph R. Cavallaro, Behnaam Aazhang, Yingyan Lin:
RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms. CoRR abs/2111.02569 (2021) - [i19]Bichen Wu, Chaojian Li, Hang Zhang, Xiaoliang Dai, Peizhao Zhang, Matthew Yu, Jialiang Wang, Yingyan Lin, Peter Vajda:
FBNetV5: Neural Architecture Search for Multiple Tasks in One Run. CoRR abs/2111.10007 (2021) - [i18]Zhongzhi Yu, Yonggan Fu, Sicheng Li, Chaojian Li, Yingyan Lin:
MIA-Former: Efficient and Robust Vision Transformers via Multi-grained Input-Adaptation. CoRR abs/2112.11542 (2021) - [i17]Haoran You, Tong Geng, Yongan Zhang, Ang Li, Yingyan Lin:
GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design. CoRR abs/2112.11594 (2021) - 2020
- [j3]Yue Wang, Jianghao Shen, Ting-Kuei Hu, Pengfei Xu, Tan M. Nguyen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin:
Dual Dynamic Inference: Enabling More Efficient, Adaptive, and Controllable Deep Inference. IEEE J. Sel. Top. Signal Process. 14(4): 623-633 (2020) - [c21]Jianghao Shen, Yue Wang, Pengfei Xu, Yonggan Fu, Zhangyang Wang, Yingyan Lin:
Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference. AAAI 2020: 5700-5708 - [c20]Chaojian Li, Tianlong Chen, Haoran You, Zhangyang Wang, Yingyan Lin:
HALO: Hardware-Aware Learning to Optimize. ECCV (9) 2020: 500-518 - [c19]Pengfei Xu, Xiaofan Zhang, Cong Hao, Yang Zhao, Yongan Zhang, Yue Wang, Chaojian Li, Zetong Guan, Deming Chen, Yingyan Lin:
AutoDNNchip: An Automated DNN Chip Predictor and Builder for Both FPGAs and ASICs. FPGA 2020: 40-50 - [c18]Yang Zhao, Chaojian Li, Yue Wang, Pengfei Xu, Yongan Zhang, Yingyan Lin:
DNN-Chip Predictor: An Analytical Performance Predictor for DNN Accelerators with Various Dataflows and Hardware Architectures. ICASSP 2020: 1593-1597 - [c17]Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin:
Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks. ICLR 2020 - [c16]Yonggan Fu, Wuyang Chen, Haotao Wang, Haoran Li, Yingyan Lin, Zhangyang Wang:
AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks. ICML 2020: 3292-3303 - [c15]Weitao Li, Pengfei Xu, Yang Zhao, Haitong Li, Yuan Xie, Yingyan Lin:
Timely: Pushing Data Movements And Interfaces In Pim Accelerators Towards Local And In Time Domain. ISCA 2020: 832-845 - [c14]Yang Zhao, Xiaohan Chen, Yue Wang, Chaojian Li, Haoran You, Yonggan Fu, Yuan Xie, Zhangyang Wang, Yingyan Lin:
SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation. ISCA 2020: 954-967 - [c13]Hongjie Wang, Yang Zhao, Chaojian Li, Yue Wang, Yingyan Lin:
A New MRAM-Based Process In-Memory Accelerator for Efficient Neural Network Training with Floating Point Precision. ISCAS 2020: 1-5 - [c12]Yonggan Fu, Haoran You, Yang Zhao, Yue Wang, Chaojian Li, Kailash Gopalakrishnan, Zhangyang Wang, Yingyan Lin:
FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training. NeurIPS 2020 - [c11]Haoran You, Xiaohan Chen, Yongan Zhang, Chaojian Li, Sicheng Li, Zihao Liu, Zhangyang Wang, Yingyan Lin:
ShiftAddNet: A Hardware-Inspired Deep Network. NeurIPS 2020 - [c10]Yingyan Lin:
Bringing Powerful Machine-Learning Systems to Daily-Life Devices via Algorithm-Hardware Co-Design. VLSI-DAT 2020: 1 - [i16]Jianghao Shen, Yonggan Fu, Yue Wang, Pengfei Xu, Zhangyang Wang, Yingyan Lin:
Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference. CoRR abs/2001.00705 (2020) - [i15]Pengfei Xu, Xiaofan Zhang, Cong Hao, Yang Zhao, Yongan Zhang, Yue Wang, Chaojian Li, Zetong Guan, Deming Chen, Yingyan Lin:
AutoDNNchip: An Automated DNN Chip Predictor and Builder for Both FPGAs and ASICs. CoRR abs/2001.03535 (2020) - [i14]Yang Zhao, Chaojian Li, Yue Wang, Pengfei Xu, Yongan Zhang, Yingyan Lin:
DNN-Chip Predictor: An Analytical Performance Predictor for DNN Accelerators with Various Dataflows and Hardware Architectures. CoRR abs/2002.11270 (2020) - [i13]Hongjie Wang, Yang Zhao, Chaojian Li, Yue Wang, Yingyan Lin:
A New MRAM-based Process In-Memory Accelerator for Efficient Neural Network Training with Floating Point Precision. CoRR abs/2003.01551 (2020) - [i12]Weitao Li, Pengfei Xu, Yang Zhao, Haitong Li, Yuan Xie, Yingyan Lin:
TIMELY: Pushing Data Movements and Interfaces in PIM Accelerators Towards Local and in Time Domain. CoRR abs/2005.01206 (2020) - [i11]Yang Zhao, Xiaohan Chen, Yue Wang, Chaojian Li, Haoran You, Yonggan Fu, Yuan Xie, Zhangyang Wang, Yingyan Lin:
SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation. CoRR abs/2005.03403 (2020) - [i10]Sicong Liu, Junzhao Du, Kaiming Nan, Zimu Zhou, Atlas Wang, Yingyan Lin:
AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles. CoRR abs/2006.04432 (2020) - [i9]Yonggan Fu, Wuyang Chen, Haotao Wang, Haoran Li, Yingyan Lin, Zhangyang Wang:
AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks. CoRR abs/2006.08198 (2020) - [i8]Haoran You, Xiaohan Chen, Yongan Zhang, Chaojian Li, Sicheng Li, Zihao Liu, Zhangyang Wang, Yingyan Lin:
ShiftAddNet: A Hardware-Inspired Deep Network. CoRR abs/2010.12785 (2020) - [i7]Yongan Zhang, Yonggan Fu, Weiwen Jiang, Chaojian Li, Haoran You, Meng Li, Vikas Chandra, Yingyan Lin:
DNA: Differentiable Network-Accelerator Co-Search. CoRR abs/2010.14778 (2020) - [i6]Yonggan Fu, Zhongzhi Yu, Yongan Zhang, Yingyan Lin:
Auto-Agent-Distiller: Towards Efficient Deep Reinforcement Learning Agents via Neural Architecture Search. CoRR abs/2012.13091 (2020) - [i5]Yonggan Fu, Haoran You, Yang Zhao, Yue Wang, Chaojian Li, Kailash Gopalakrishnan, Zhangyang Wang, Yingyan Lin:
FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training. CoRR abs/2012.13113 (2020)
2010 – 2019
- 2019
- [c9]Pengfei Xu, Yue Wang, Yang Zhao, Yingyan Lin:
Live Demonstration: Bringing Powerful Deep Learning into Daily-Life Devices (Mobiles and FPGAs) Via Deep k-Means. ISCAS 2019: 1 - [c8]Yue Wang, Ziyu Jiang, Xiaohan Chen, Pengfei Xu, Yang Zhao, Yingyan Lin, Zhangyang Wang:
E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings. NeurIPS 2019: 5139-5151 - [i4]Yue Wang, Jianghao Shen, Ting-Kuei Hu, Pengfei Xu, Tan M. Nguyen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin:
Dual Dynamic Inference: Enabling More Efficient, Adaptive and Controllable Deep Inference. CoRR abs/1907.04523 (2019) - [i3]Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Yingyan Lin, Zhangyang Wang, Richard G. Baraniuk:
Drawing early-bird tickets: Towards more efficient training of deep networks. CoRR abs/1909.11957 (2019) - [i2]Yue Wang, Ziyu Jiang, Xiaohan Chen, Pengfei Xu, Yang Zhao, Yingyan Lin, Zhangyang Wang:
E2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Saving. CoRR abs/1910.13349 (2019) - 2018
- [j2]Yingyan Lin, Sai Zhang, Naresh R. Shanbhag:
A Rank Decomposed Statistical Error Compensation Technique for Robust Convolutional Neural Networks in the Near Threshold Voltage Regime. J. Signal Process. Syst. 90(10): 1439-1451 (2018) - [c7]Junru Wu, Yue Wang, Zhenyu Wu, Zhangyang Wang, Ashok Veeraraghavan, Yingyan Lin:
Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions. ICML 2018: 5359-5368 - [c6]Yingyan Lin, Joseph R. Cavallaro:
Energy-efficient Convolutional Neural Networks via Statistical Error Compensated Near Threshold Computing. ISCAS 2018: 1-5 - [c5]Riccardo Petrolo, Yingyan Lin, Edward W. Knightly:
ASTRO: Autonomous, Sensing, and Tetherless netwoRked drOnes. DroNet@MobiSys 2018: 1-6 - [c4]Sicong Liu, Yingyan Lin, Zimu Zhou, Kaiming Nan, Hui Liu, Junzhao Du:
On-Demand Deep Model Compression for Mobile Devices: A Usage-Driven Model Selection Framework. MobiSys 2018: 389-400 - [i1]Junru Wu, Yue Wang, Zhenyu Wu, Zhangyang Wang, Ashok Veeraraghavan, Yingyan Lin:
Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions. CoRR abs/1806.09228 (2018) - 2017
- [c3]Yingyan Lin, Charbel Sakr, Yongjune Kim, Naresh R. Shanbhag:
PredictiveNet: An energy-efficient convolutional neural network via zero prediction. ISCAS 2017: 1-4 - 2016
- [j1]Yingyan Lin, Min-Sun Keel, Adam C. Faust, Aolin Xu, Naresh R. Shanbhag, Elyse Rosenbaum, Andrew C. Singer:
A Study of BER-Optimal ADC-Based Receiver for Serial Links. IEEE Trans. Circuits Syst. I Regul. Pap. 63-I(5): 693-704 (2016) - [c2]Yingyan Lin, Sai Zhang, Naresh R. Shanbhag:
Variation-Tolerant Architectures for Convolutional Neural Networks in the Near Threshold Voltage Regime. SiPS 2016: 17-22 - 2012
- [c1]Aadithya V. Karthik, Yingyan Lin, Chenjie Gu, Aolin Xu, Jaijeet S. Roychowdhury, Naresh R. Shanbhag:
A fully automated technique for constructing FSM abstractions of non-ideal latches in communication systems. ICASSP 2012: 5289-5292
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last updated on 2022-08-10 22:57 CEST by the dblp team
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