受强制性开放获取政策约束的文章 - Zhe Li了解详情
可在其他位置公开访问的文章：12 篇
CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices
C Ding, S Liao, Y Wang, Z Li, N Liu, Y Zhuo, C Wang, X Qian, Y Bai, ...
Proceedings of the 50th Annual IEEE/ACM International Symposium on …, 2017
强制性开放获取政策： US National Science Foundation, US Department of Defense
Sc-dcnn: Highly-scalable deep convolutional neural network using stochastic computing
A Ren, Z Li, C Ding, Q Qiu, Y Wang, J Li, X Qian, B Yuan
ASPLOS 2017 - 22nd International Conference on Architectural Support for …, 2017
强制性开放获取政策： US Department of Defense, 国家自然科学基金委员会, Government of Spain
C-LSTM: Enabling efficient LSTM using structured compression techniques on FPGAs
S Wang, Z Li, C Ding, B Yuan, Q Qiu, Y Wang, Y Liang
Proceedings of the 2018 ACM/SIGDA International Symposium on Field …, 2018
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
HEIF: Highly efficient stochastic computing-based inference framework for deep neural networks
Z Li, J Li, A Ren, R Cai, C Ding, X Qian, J Draper, B Yuan, J Tang, Q Qiu, ...
IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2018
强制性开放获取政策： US National Science Foundation, US Department of Defense, 国家自然科学基金委 …
E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs
Z Li, C Ding, S Wang, W Wen, Y Zhuo, C Liu, Q Qiu, W Xu, X Lin, X Qian, ...
25th IEEE International Symposium on High-Performance Computer Architecture, 2019
强制性开放获取政策： US National Science Foundation
Towards ultra-high performance and energy efficiency of deep learning systems: an algorithm-hardware co-optimization framework
Y Wang, C Ding, Z Li, G Yuan, S Liao, X Ma, B Yuan, X Qian, J Tang, ...
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
强制性开放获取政策： US National Science Foundation
Energy-Efficient, High-Performance, Highly-Compressed Deep Neural Network Design using Block-Circulant Matrices
S Liao, Z Li, X Lin, Q Qiu, Y Wang, B Yuan
2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 458-465, 2017
强制性开放获取政策： US National Science Foundation, US Department of Defense
CircConv: A Structured Convolution with Low Complexity
BY Siyu Liao, Zhe Li, Liang Zhao, Qinru Qiu, Yanzhi Wang
Proceedings of the AAAI Conference on Artificial Intelligence 33, 4287-4294, 2019
强制性开放获取政策： US National Science Foundation
An Area and Energy Efficient Design of Domain-Wall Memory-Based Deep Convolutional Neural Networks using Stochastic Computing
X Ma, Y Zhang, G Yuan, A Ren, Z Li, J Han, J Hu, Y Wang
2018 19th International Symposium on Quality Electronic Design (ISQED), 2018
强制性开放获取政策： US National Science Foundation
Fast and accurate trajectory tracking for unmanned aerial vehicles based on deep reinforcement learning
Y Li, H Li, Z Li, H Fang, AK Sanyal, Y Wang, Q Qiu
2019 IEEE 25th International Conference on Embedded and Real-Time Computing …, 2019
强制性开放获取政策： US National Science Foundation
A neuromorphic architecture for context aware text image recognition
Q Qiu, Z Li, K Ahmed, W Liu, SF Habib, H Li, M Hu
Journal of Signal Processing Systems 84, 355-369, 2016
强制性开放获取政策： US National Science Foundation
Towards parallel implementation of associative inference for cogent confabulation
Z Li, Q Qiu, M Tamhankar
2016 IEEE High Performance Extreme Computing Conference (HPEC), 1-6, 2016
强制性开放获取政策： US National Science Foundation
出版信息和资助信息由计算机程序自动确定