Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding S Han, H Mao, WJ Dally arXiv preprint arXiv:1510.00149, 2015 | 10114 | 2015 |
EIE: Efficient inference engine on compressed deep neural network S Han, X Liu, H Mao, J Pu, A Pedram, MA Horowitz, WJ Dally ACM SIGARCH Computer Architecture News 44 (3), 243-254, 2016 | 3107 | 2016 |
Deep gradient compression: Reducing the communication bandwidth for distributed training Y Lin, S Han, H Mao, Y Wang, WJ Dally arXiv preprint arXiv:1712.01887, 2017 | 1463 | 2017 |
Trained ternary quantization C Zhu, S Han, H Mao, WJ Dally arXiv preprint arXiv:1612.01064, 2016 | 1276 | 2016 |
ESE: Efficient speech recognition engine with sparse lstm on fpga S Han, J Kang, H Mao, Y Hu, X Li, Y Li, D Xie, H Luo, S Yao, Y Wang, ... Proceedings of the 2017 ACM/SIGDA International Symposium on Field …, 2017 | 796 | 2017 |
Exploring the granularity of sparsity in convolutional neural networks H Mao, S Han, J Pool, W Li, X Liu, Y Wang, WJ Dally Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 491* | 2017 |
Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding. arXiv 2015 S Han, H Mao, WJ Dally arXiv preprint arXiv:1510.00149, 0 | 331 | |
DSD: Regularizing deep neural networks with dense-sparse-dense training flow S Han, J Pool, S Narang, H Mao, S Tang, E Elsen, B Catanzaro, J Tran, ... arXiv preprint arXiv:1607.04381, 2016 | 323* | 2016 |
Towards Real-Time Object Detection on Embedded Systems Huizi Mao, Song Yao, Tianqi Tang, Boxun Li, Jun Yao, Yu Wang IEEE Transactions on Emerging Topics in Computing 99 (99), 1-1, 2016 | 99* | 2016 |
Deep compression and EIE: Efficient inference engine on compressed deep neural network. S Han, X Liu, H Mao, J Pu, A Pedram, M Horowitz, B Dally Hot Chips Symposium, 1-6, 2016 | 58 | 2016 |
Deep compression: Compressing deep neural network with pruning S Han, H Mao, WJ Dally Trained Quantization and Huffman Coding. arXiv 1510, v5, 2015 | 55 | 2015 |
A Delay Metric for Video Object Detection: What Average Precision Fails to Tell H Mao, X Yang, WJ Dally 2019 International Conference on Computer Vision (ICCV), 2019 | 46 | 2019 |
Real-time object detection towards high power efficiency J Yu, K Guo, Y Hu, X Ning, J Qiu, H Mao, S Yao, T Tang, B Li, Y Wang, ... 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE), 704-708, 2018 | 29 | 2018 |
CaTDet: Cascaded Tracked Detector for Efficient Object Detection from Video H Mao, T Kong, WJ Dally 2019 The Conference on Systems and Machine Learning (SysML), 2019 | 28 | 2019 |
Rebooting computing and low-power image recognition challenge YH Lu, AM Kadin, AC Berg, TM Conte, EP DeBenedictis, R Garg, ... 2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 927-932, 2015 | 22 | 2015 |
PatchNet--Short-range Template Matching for Efficient Video Processing H Mao, S Zhu, S Han, WJ Dally arXiv preprint arXiv:2103.07371, 2021 | 7 | 2021 |
Retrospective: Eie: Efficient inference engine on sparse and compressed neural network S Han, X Liu, H Mao, J Pu, A Pedram, MA Horowitz, WJ Dally arXiv preprint arXiv:2306.09552, 2023 | 3 | 2023 |
Methods and Metrics for Efficient Video Object Detection H Mao Stanford University, 2021 | | 2021 |