Applications in Deep Learning
(CV, NLP, RL)
- Prior-aware Neural Network for Partially-Supervised Multi-Organ Segmentation
Yuyin Zhou*, Zhe Li*, Song Bai*, Chong Wang, Xinlei Chen, Mei Han, Elliot Fishman, Alan Yuille
ICCV 2019 [pdf] - Learning Topics using Semantic Locality
Ziyi Zhao, Krittaphat Pugdeethosapol, Sheng Lin, Zhe Li, Caiwen Ding, Yanzhi Wang, Qinru Qiu
ICPR 2018 [pdf] - Thoracic Disease Identification and Localization with Limited Supervision
Zhe Li, Chong Wang, Mei Han, Yuan Xue, Wei Wei, Li-Jia Li, Li Fei-Fei
CVPR 2018 [pdf] - Hierarchical Framework of Cloud Resource Allocation and Power Management Using Deep Reinforcement Learning
Zhe Li*, Ning Liu*, Zhiyuan Xu*, Jielong Xu, Sheng Lin, Qinru Qiu, Jian Tang and Yanzhi Wang
ICDCS 2017 [pdf] (acceptance rate: 16.9%)
Deep Learning Acceleration using Circulant Matrix
- CircConv: A Structured Convolution with Low Complexity
Zhe Li*, Siyu Liao, Liang Zhao, Qinru Qiu, Yanzhi Wang, Bo Yuan
AAAI 2019 [pdf] - E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs
Zhe Li, Caiwen Ding, Siyue Wang, Wujie Wen, Youwei Zhuo, etc.
HPCA 2019 [pdf] - Efficient Recurrent Neural Networks using Structured Matrices in FPGAs
Zhe Li, Shuo Wang, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Yun Liang
ICLR 2018 workshop [pdf] - Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework
Yanzhi Wang, Caiwen Ding, Zhe Li, Geng Yuan, Siyu Liao, Xiaolong Ma, Bo Yuan, Xuehai Qian, Jian Tang, Qinru Qiu, Xue Lin
AAAI 2018 [pdf] (acceptance rate: 25%) - C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs
Zhe Li*, Shuo Wang*, Caiwen Ding*, Bo Yuan, Qinru Qiu, Yanzhi Wang, Yun Liang
FPGA 2018 [pdf] [code] (acceptance rate: 25%) - CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-Circulant Weight Matrices
Caiwen Ding*, Siyu Liao*, Yanzhi Wang*, Zhe Li, Ning Liu, Youwei Zhuo, Chao Wang et al.
MICRO 2017 [pdf] (acceptance rate: 18.6%) - Energy-Efficient, High-Performance, Highly-Compressed Deep Neural Network Design using Block-Circulant Matrices
Zhe Li*, Siyu Liao*, Xue Lin, Qinru Qiu, Yanzhi Wang, Bo Yuan
ICCAD 2017 [pdf] - Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank
Liang Zhao, Siyu Liao, Yanzhi Wang, Zhe Li, Jian Tang, Victor Pan, Bo Yuan
ICML 2017 [pdf] (acceptance rate: 22%, Oral Presentation)
Deep Learning Acceleration using Stochastic Computing
- HEIF: Highly Efficient Stochastic Computing based Inference Framework for Deep Neural Networks
Zhe Li, Ji Li, Ao Ren, Ruizhe Cai, Caiwen Ding, Xuehai Qian, Jeffrey Draper, Bo Yuan, Jian Tang, Qinru Qiu, Yanzhi Wang
IEEE Transactions on Computer Aided Design of Integrated Circuits & Systems [pdf] - An Area and Energy Efficient Design of Domain-Wall Memory-Based Deep Convolutional Neural Networks using Stochastic Computing
Xiaolong Ma*, Yipeng Zhang*, Geng Yuan, Ao Ren, Zhe Li, Jie Han, Jingtong Hu, Yanzhi Wang
ISQED 2018 [pdf] (Best paper nomination) - Normalization and dropout for stochastic computing-based deep convolutional neural networks
Ji Li, Zihao Yuan, Zhe Li, Ao Ren, Caiwen Ding, Jeffrey Draper, Shahin Nazarian, Qinru Qiu, Bo Yuan, Yanzhi Wang
Integration, the VLSI Journal [pdf] - Softmax Regression Design for Stochastic Computing Based Deep Convolutional Neural Networks
Zihao Yuan, Ji Li, Zhe Li, Caiwen Ding, Ao Ren, Bo Yuan, Qinru Qiu, Jeffrey Draper, Yanzhi Wang
GLVLSI 2017 [pdf] (acceptance rate: 24.4%) - Hardware-Driven Nonlinear Activation for Stochastic Computing Based Deep Convolutional Neural Networks
Ji Li, Zihao Yuan, Zhe Li, Caiwen Ding, Ao Ren, Qinru Qiu, Jeffrey Draper, Yanzhi Wang
IJCNN 2017 [pdf] - Structural Design Optimization for Deep Convolutional Neural Networks using Stochastic Computing
Zhe Li, Ao Ren, Ji Li, Qinru Qiu, Bo Yuan, Jeffrey Draper, Yanzhi Wang
DATE 2017 [pdf] - SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing
Ao Ren, Ji Li, Zhe Li, Caiwen Ding, Xuehai Qian, Qinru Qiu, Bo Yuan, Yanzhi Wang
ASPLOS 2017 [pdf] (acceptance rate: 17.4%) - Towards Acceleration of Deep Convolutional Neural Networks using Stochastic Computing
Ji Li, Ao Ren, Zhe Li, Caiwen Ding, Bo Yuan, Qinru Qiu, Yanzhi Wang
ASPDAC 2017 [pdf] - DSCNN: Hardware-Oriented Optimization for Stochastic Computing Based Deep Convolutional Neural Networks
Zhe Li*, Ao Ren*, Ji Li, Qinru Qiu, Yanzhi Wang, and Bo Yuan
ICCD 2016 [pdf] - Designing reconfigurable large-scale deep learning systems using stochastic computing
Zhe Li*, Ao Ren*, Yanzhi Wang, Qinru Qiu, and Bo Yuan
ICRC 2016 [pdf]
Neuromorphic Computing
- Efficient Cloud Resource Management using Neuromorphic Modeling and Prediction for Virtual Machine Resource Utilization
Zhe Li, Xiaolong Ma, Ji Li, Jian Tang, Qinru Qiu, and Yanzhi Wang
ICESS 2019 [pdf] - Probabilistic Inference in Neuromorphic Architecture: Applications and Implementations
Zhe Li, Yanzhi Wang, Qinru Qiu
ICCAD 2016 HALO [poster] - Assisting Fuzzy Offline Handwriting Recognition Using Recurrent Belief Propagation
Yilan Li, Zhe Li, Qinru Qiu
SSCI 2016 [pdf] - Towards Parallel Implementation of Associative Inference for Cogent Confabulation
Zhe Li, Qinru Qiu, and Mangesh Tamhankar.
HPEC 2016 [pdf] (Most Innovative Student Paper Award, Best Paper Finalist) - A Neuromorphic Architecture for Context Aware Text Image Recognition
Qinru Qiu,Zhe Li, Khadeer Ahmed, Wei Liu, Syed Faisal Habib, Hai (Helen) Li, Miao Hu
Journal of Signal Processing Systems (2015) [pdf] (corresponding author) - Neuromorphic acceleration for context aware text image recognition
Qinru Qiu, Zhe Li, Khandakar Ahmed, Hai Li, and Miao Hu
SiPS Workshop 2014 [pdf] (corresponding author) - Completion and parsing Chinese sentences using cogent confabulation
Zhe Li, and Qinru Qiu
SSCI 2014 [pdf]
Others
- Developing a disaster surveillance system based on wireless sensor network and cloud platform
Jianhu Cen, Tao Yu, Zhe Li, Song Jin, and Shaohua Liu
ICCTA 2011 [pdf]
*Equal Contribution