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Yingyezhe Jin
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2020 – today
- 2021
- [c9]Teng Xu, Gerard Goossen, Huseyin Kerem Cevahir, Sara Khodeir, Yingyezhe Jin, Frank Li, Shawn Shan, Sagar Patel, David Freeman, Paul Pearce:
Deep Entity Classification: Abusive Account Detection for Online Social Networks. USENIX Security Symposium 2021: 4097-4114
2010 – 2019
- 2018
- [j3]Yu Liu, Yingyezhe Jin, Peng Li:
Online Adaptation and Energy Minimization for Hardware Recurrent Spiking Neural Networks. ACM J. Emerg. Technol. Comput. Syst. 14(1): 11:1-11:21 (2018) - [c8]Bon Woong Ku, Yu Liu, Yingyezhe Jin, Sandeep Kumar Samal, Peng Li, Sung Kyu Lim
:
Design and architectural co-optimization of monolithic 3D liquid state machine-based neuromorphic processor. DAC 2018: 165:1-165:6 - [c7]Bon Woong Ku, Yu Liu, Yingyezhe Jin, Peng Li, Sung Kyu Lim
Area-efficient and low-power face-to-face-bonded 3D liquid state machine design. ICCAD 2018: 121 - [c6]Yingyezhe Jin, Wenrui Zhang
Hybrid Macro/Micro Level Backpropagation for Training Deep Spiking Neural Networks. NeurIPS 2018: 7005-7015 - [i1]Yingyezhe Jin, Peng Li, Wenrui Zhang:
Hybrid Macro/Micro Level Backpropagation for Training Deep Spiking Neural Networks. CoRR abs/1805.07866 (2018) - 2017
- [j2]Yingyezhe Jin, Peng Li:
Performance and robustness of bio-inspired digital liquid state machines: A case study of speech recognition. Neurocomputing 226: 145-160 (2017) - [c5]Yingyezhe Jin, Peng Li:
Calcium-modulated supervised spike-timing-dependent plasticity for readout training and sparsification of the liquid state machine. IJCNN 2017: 2007-2014 - [c4]Yu Liu, Yingyezhe Jin, Peng Li:
Exploring sparsity of firing activities and clock gating for energy-efficient recurrent spiking neural processors. ISLPED 2017: 1-6 - 2016
- [c3]Yingyezhe Jin, Peng Li:
AP-STDP: A novel self-organizing mechanism for efficient reservoir computing. IJCNN 2016: 1158-1165 - [c2]Yingyezhe Jin, Yu Liu, Peng Li:
SSO-LSM: A Sparse and Self-Organizing architecture for Liquid State Machine based neural processors. NANOARCH 2016: 55-60 - 2015
- [j1]Yong Zhang, Peng Li, Yingyezhe Jin, Yoonsuck Choe:
A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition. IEEE Trans. Neural Networks Learn. Syst. 26(11): 2635-2649 (2015) - [c1]Qian Wang, Yingyezhe Jin, Peng Li:
General-purpose LSM learning processor architecture and theoretically guided design space exploration. BioCAS 2015: 1-4
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