| Hybrid macro/micro level backpropagation for training deep spiking neural networks Y Jin, W Zhang, P Li Advances in neural information processing systems 31, 2018 | 227 | 2018 |
| A digital liquid state machine with biologically inspired learning and its application to speech recognition Y Zhang, P Li, Y Jin, Y Choe IEEE transactions on neural networks and learning systems 26 (11), 2635-2649, 2015 | 204 | 2015 |
| Deep entity classification: Abusive account detection for online social networks T Xu, G Goossen, HK Cevahir, S Khodeir, Y Jin, F Li, S Shan, S Patel, ... 30th {USENIX} Security Symposium ({USENIX} Security 21), 2021 | 50 | 2021 |
| General-purpose LSM learning processor architecture and theoretically guided design space exploration Q Wang, Y Jin, P Li 2015 IEEE Biomedical Circuits and Systems Conference (BioCAS), 1-4, 2015 | 48 | 2015 |
| Performance and robustness of bio-inspired digital liquid state machines: A case study of speech recognition Y Jin, P Li Neurocomputing 226, 145-160, 2017 | 39 | 2017 |
| SSO-LSM: A sparse and self-organizing architecture for liquid state machine based neural processors Y Jin, Y Liu, P Li 2016 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH …, 2016 | 35 | 2016 |
| AP-STDP: A novel self-organizing mechanism for efficient reservoir computing Y Jin, P Li 2016 International Joint Conference on Neural Networks (IJCNN), 1158-1165, 2016 | 34 | 2016 |
| Online adaptation and energy minimization for hardware recurrent spiking neural networks Y Liu, Y Jin, P Li ACM Journal on Emerging Technologies in Computing Systems (JETC) 14 (1), 1-21, 2018 | 18 | 2018 |
| Design and architectural co-optimization of monolithic 3d liquid state machine-based neuromorphic processor BW Ku, Y Liu, Y Jin, S Samal, P Li, SK Lim Proceedings of the 55th Annual Design Automation Conference, 1-6, 2018 | 13 | 2018 |
| Exploring sparsity of firing activities and clock gating for energy-efficient recurrent spiking neural processors Y Liu, Y Jin, P Li 2017 IEEE/ACM International Symposium on Low Power Electronics and Design …, 2017 | 8 | 2017 |
| Calcium-modulated supervised spike-timing-dependent plasticity for readout training and sparsification of the liquid state machine Y Jin, P Li 2017 International Joint Conference on Neural Networks (IJCNN), 2007-2014, 2017 | 7 | 2017 |
| Architectures and Training Algorithms of Deep Spiking Neural Networks Y Jin Texas A&M University, 2018 | 1 | 2018 |
| Area-efficient and Low-power Face-to-Face-bonded 3D Liquid State Machine Design BW Ku, Y Liu, Y Jin, P Li, SK Lim 2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 1-6, 2018 | | 2018 |
| Online adaptation and energy minimization for hardware recurrent Y Liu, Y Jin, P Li | | 2018 |
| A digital liquid state machine with biologically inspired learning and its application to speech Y Zhang, P Li, Y Jin | | 2015 |
Peng LiProfessor of Electrical & Computer Engineering, University of California, Santa Barbara在 ucsb.edu 的电子邮件经过验证
