


default search action
Peng Li 0001
Person information
- affiliation: University of California, Santa Barbara, CA, USA
- affiliation: Texas A&M University, College Station, TX, USA
- affiliation (PhD 2003): Carnegie Mellon University, Pittsburgh, PA, USA
Other persons with the same name
- Peng Li — disambiguation page
- Peng Li 0002
— Shandong University, School of Control Science and Engineering, Jinan, China
- Peng Li 0003
— Chinese Academy of Sciences, Institute of Geographic Sciences and Natural Resources Research, Beijing, China
- Peng Li 0004
— Northwest A&F University, College of Life Science, Yangling, Shaanxi, China
- Peng Li 0005
— University of Alberta, Nanofab, Edmonton, AB, Canada
- Peng Li 0006
— University of Strathclyde, Electronic and Electrical Engineering Department, Glasgow, UK
- Peng Li 0007
— Beijing Jiaotong University, School of Electronic and Information Engineering, China
- Peng Li 0008
— North China Electric Power University, School of Economics and Management, Beijing, China
- Peng Li 0009
— Harbin University of Commerce, School of Management, China
- Peng Li 0010
— University of Wollongong, School of Mathematics & Applied Statistics, NSW, Australia (and 2 more)
- Peng Li 0011
— Nanjing University of Posts and Telecommunications, School of Computer Science and Technology, China (and 1 more)
- Peng Li 0012
— Chinese Academy of Sciences, Institute of Semiconductors, Beijing, China
- Peng Li 0013
— Hunan University of Technology, College of Electrical and Information Engineering, Zhuzhou, China
- Peng Li 0014
— Tianjin University, Key Laboratory of Smart Grid of the Ministry of Education, China (and 1 more)
- Peng Li 0015
— National University of Defense Technology, College of Mechatronics Engineering and Automation, Changsha, China
- Peng Li 0016
— Shaanxi Normal University, School of Computer Science, China (and 2 more)
- Peng Li 0017
— University of Aizu, School of Computer Science and Engineering, Aizuwakamatsu, Japan
- Peng Li 0018 — PUC-Rio Rio de Janeiro, Brazil (and 2 more)
- Peng Li 0019
— Harbin Institute of Technology, Shenzhen Graduate School, School of Mechatronical Engineering, China (and 3 more)
- Peng Li 0020 — Microsoft Corporation, Redmond, WA, USA (and 1 more)
- Peng Li 0021 — Chinese Academy of Sciences, Institute of Information Engineering, Beijing, China
- Peng Li 0022 — Halliburton Energy Services Inc., Houston, TX, USA
- Peng Li 0023 — University of Houston, Department of Mechanical Engineering, TX, USA
- Peng Li 0024
— Imperial College London, Department of Electrical and Electronic Engineering, UK
- Peng Li 0025
— China Academy of Engineering Physics, Beijing, China
- Peng Li 0026 — ByteDance Inc., Beijing, China (and 1 more)
- Peng Li 0027
— Dalian University of Technology, School of Software Technology, China (and 1 more)
- Peng Li 0028 — Intel Corporation, Hillsboro, OR, USA (and 1 more)
- Peng Li 0029
— Harbin Engineering University, Acoustic Science and Technology Laboratory / College of Underwater Acoustic Engineering, China
- Peng Li 0030
— Tsinghua University, Institute for AI Industry Research (AIR), Beijing, China (and 3 more)
- Peng Li 0031
— Tsinghua University, Suzhou Automotive Research Institute, Vehicle Technology Group, Beijing, China (and 3 more)
- Peng Li 0032 — Chinese Academy of Sciences, Institute of Automation, Beijing, China
- Peng Li 0033 — University of Texas at Dallas, Department of Computer Science, Richardson, TX, USA
- Peng Li 0034
— Zhejiang University, College of Optical Science and Engineering, State Key Laboratory of Modern Optical Instrumentation, China
- Peng Li 0035
— China University of Petroleum (East China), College of Information and Control Engineering, Qingdao, China
- Peng Li 0036
— Xi'an University of Technology, School of Computer Science and Engineering, China (and 1 more)
- Peng Li 0037
— Dalian Polytechnic University, School of Information Science and Engineering, China (and 1 more)
- Peng Li 0038
— Chinese Academy of Sciences, Technology and Engineering Center for Space Utilization, Beijing, China
- Peng Li 0039
— Yunnan University, School of Information, Kunming, China
- Peng Li 0040
— Chuzhou University, School of Geographic Information and Tourism, China
- Peng Li 0041
— Center for Disease Control and Prevention of PLA, Beijing, China
- Peng Li 0042
— North China Electric Power University, Key Lab of Condition Monitoring and Control for Power Plant Equipment, Baoding, China
- Peng Li 0043
— Yanshan University, Institute of Electrical Engineering, Qinhuangdao, China
- Peng Li 0044
— Xi'an University of Technology, Faculty of Economics and Management, China (and 1 more)
- Peng Li 0045
— Ostwestfalen-Lippe University of Applied Science, inIT, Lemgo, Germany
- Peng Li 0046
— Wuhan University of Science and Technology, College of Computer Science and Technology / Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, China (and 1 more)
- Peng Li 0047 — Geo-Centers, Inc., USA
- Peng Li 0048 — France Telecom Orange Labs (Beijing), China
- Peng Li 0049 — Shandong University of Science and Technology, College of Computer Science and Engineering, Qingdao, China
- Peng Li 0050
— North China Electric Power University, Department of Mathematics and Physics, Baoding, China (and 1 more)
- Peng Li 0051
— Beijing University of Technology, Faculty of Information Technology, Department of Automation, China (and 1 more)
- Peng Li 0052
— University of Science and Technology Beijing, School of Computer and Communication Engineering, China
- Peng Li 0053
— Power China Zhongnan Engineering Corporation Ltd., China (and 2 more)
- Peng Li 0054
— Xiangtan University, School of Information Engineering, China (and 1 more)
- Peng Li 0055 — Loughborough University, UK
- Peng Li 0056 — Alibaba Group, Hangzhou, China (and 2 more)
- Peng Li 0057
— Beijing University of Technology, China (and 3 more)
- Peng Li 0058 — University of Utah, School of Computing, UT, USA
- Peng Li 0059 — University of North Carolina, Chapel Hill, USA
- Peng Li 0060
— Ocean University of China, Institute of Estuarine and Coastal Zone, College of Marine Geosciences, Qingdao, China
Refine list

refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [j78]Karthik Somayaji N. S., Yu Wang, Malachi Schram, Ján Drgona, Mahantesh M. Halappanavar, Frank Liu, Peng Li:
Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory. Trans. Mach. Learn. Res. 2024 (2024) - [j77]Karthik Somayaji Nanjangud Suryanarayana
, Peng Li
:
Pareto Optimization of Analog Circuits Using Reinforcement Learning. ACM Trans. Design Autom. Electr. Syst. 29(2): 37:1-37:14 (2024) - [c138]Yu Wang, Yuxuan Yin, Karthik Somayaji N. S., Ján Drgona, Malachi Schram, Mahantesh Halappanavar, Frank Liu, Peng Li:
Semi-supervised Learning of Dynamical Systems with Neural Ordinary Differential Equations: A Teacher-Student Model Approach. AAAI 2024: 15698-15705 - [c137]Yuxuan Yin
, Rebecca Chen
, Chen He
, Peng Li
:
Data-Efficient Conformalized Interval Prediction of Minimum Operating Voltage Capturing Process Variations. DAC 2024: 308:1-308:6 - [c136]Zihu Wang
, Karthik Somayaji N. S.
, Peng Li
:
Learn-by-Compare: Analog Performance Prediction using Contrastive Regression with Design Knowledge. DAC 2024: 318:1-318:6 - [c135]Zihu Wang
, Lingqiao Liu
, Scott Ricardo Figueroa Weston, Samuel Tian, Peng Li
:
On Learning Discriminative Features from Synthesized Data for Self-supervised Fine-Grained Visual Recognition. ECCV (89) 2024: 101-117 - [c134]Yuxuan Yin, Yu Wang, Peng Li:
High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling. ICML 2024 - [c133]Jeongjun Lee
, Peng Li
:
Systolic Array Acceleration of Spiking Neural Networks with Application-Independent Split-Time Temporal Coding. ISLPED 2024: 1-6 - [i26]Yuxuan Yin, Xiaoxiao Wang, Rebecca Chen, Chen He, Peng Li:
Reliable Interval Prediction of Minimum Operating Voltage Based on On-chip Monitors via Conformalized Quantile Regression. CoRR abs/2406.18536 (2024) - [i25]Yuxuan Yin, Yu Wang, Boxun Xu, Peng Li:
ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Models. CoRR abs/2406.18770 (2024) - [i24]Zihu Wang, Lingqiao Liu, Scott Ricardo Figueroa Weston, Samuel Tian, Peng Li:
On Learning Discriminative Features from Synthesized Data for Self-Supervised Fine-Grained Visual Recognition. CoRR abs/2407.14676 (2024) - [i23]Yu Wang, Yuxuan Yin, Peng Li:
Towards the Mitigation of Confirmation Bias in Semi-supervised Learning: a Debiased Training Perspective. CoRR abs/2409.18316 (2024) - [i22]Boxun Xu, Junyoung Hwang, Pruek Vanna-Iampikul, Sung Kyu Lim, Peng Li:
Spiking Transformer Hardware Accelerators in 3D Integration. CoRR abs/2411.07397 (2024) - [i21]Boxun Xu, Junyoung Hwang, Pruek Vanna-Iampikul, Yuxuan Yin, Sung Kyu Lim, Peng Li:
Towards 3D Acceleration for low-power Mixture-of-Experts and Multi-Head Attention Spiking Transformers. CoRR abs/2412.05540 (2024) - 2023
- [j76]Ling Liang
, Xing Hu, Lei Deng
, Yujie Wu, Guoqi Li
, Yufei Ding
, Peng Li
, Yuan Xie
:
Exploring Adversarial Attack in Spiking Neural Networks With Spike-Compatible Gradient. IEEE Trans. Neural Networks Learn. Syst. 34(5): 2569-2583 (2023) - [j75]Lei Deng
, Yujie Wu, Yifan Hu, Ling Liang
, Guoqi Li
, Xing Hu, Yufei Ding
, Peng Li
, Yuan Xie
:
Comprehensive SNN Compression Using ADMM Optimization and Activity Regularization. IEEE Trans. Neural Networks Learn. Syst. 34(6): 2791-2805 (2023) - [c132]Yu Wang, Ján Drgona, Jiaxin Zhang, Karthik Somayaji Nanjangud Suryanarayana, Malachi Schram, Frank Liu, Peng Li:
AutoNF: Automated Architecture Optimization of Normalizing Flows with Unconstrained Continuous Relaxation Admitting Optimal Discrete Solution. AAAI 2023: 10244-10252 - [c131]Yuxuan Yin, Rebecca Chen, Chen He
, Peng Li:
Domain-Specific Machine Learning Based Minimum Operating Voltage Prediction Using On-Chip Monitor Data. ITC 2023: 99-104 - [c130]Zihu Wang, Hanbin Hu, Chen He
, Peng Li:
Recognizing Wafer Map Patterns Using Semi-Supervised Contrastive Learning with Optimized Latent Representation Learning and Data Augmentation. ITC 2023: 141-150 - [i20]Zihu Wang, Yu Wang, Hanbin Hu, Peng Li:
Contrastive Learning with Consistent Representations. CoRR abs/2302.01541 (2023) - [i19]Yuxuan Yin, Yu Wang, Peng Li:
High-dimensional Bayesian Optimization via Semi-supervised Learning with Optimized Unlabeled Data Sampling. CoRR abs/2305.02614 (2023) - [i18]Karthik Somayaji N. S., Yu Wang, Malachi Schram
, Ján Drgona, Mahantesh Halappanavar, Frank Liu, Peng Li:
Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory. CoRR abs/2308.13011 (2023) - [i17]Yu Wang, Yuxuan Yin, Karthik Somayaji Nanjangud Suryanarayana, Ján Drgona, Malachi Schram, Mahantesh Halappanavar, Frank Liu, Peng Li:
Semi-Supervised Learning of Dynamical Systems with Neural Ordinary Differential Equations: A Teacher-Student Model Approach. CoRR abs/2310.13110 (2023) - 2022
- [j74]Jeong-Jun Lee
, Wenrui Zhang
, Yuan Xie
, Peng Li
:
SaARSP: An Architecture for Systolic-Array Acceleration of Recurrent Spiking Neural Networks. ACM J. Emerg. Technol. Comput. Syst. 18(4): 68:1-68:23 (2022) - [j73]Ling Liang
, Zheng Qu
, Zhaodong Chen
, Fengbin Tu
, Yujie Wu, Lei Deng
, Guoqi Li
, Peng Li
, Yuan Xie
:
H2Learn: High-Efficiency Learning Accelerator for High-Accuracy Spiking Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(11): 4782-4796 (2022) - [c129]Jeong-Jun Lee, Wenrui Zhang, Peng Li:
Parallel Time Batching: Systolic-Array Acceleration of Sparse Spiking Neural Computation. HPCA 2022: 317-330 - 2021
- [j72]Wenrui Zhang, Peng Li:
Skip-Connected Self-Recurrent Spiking Neural Networks With Joint Intrinsic Parameter and Synaptic Weight Training. Neural Comput. 33(7): 1886-1913 (2021) - [j71]Yin Sheng
, Tingwen Huang
, Zhigang Zeng
, Peng Li:
Exponential Stabilization of Inertial Memristive Neural Networks With Multiple Time Delays. IEEE Trans. Cybern. 51(2): 579-588 (2021) - [c128]Yu Wang, Peng Li:
Algorithm and Hardware Co-Design for FPGA Acceleration of Hamiltonian Monte Carlo Based No-U-Turn Sampler. ASAP 2021: 9-16 - [c127]Myung Seok Shim, Hanbin Hu
, Peng Li:
Reversible Gating Architecture for Rare Failure Detection of Analog and Mixed-Signal Circuits. DAC 2021: 901-906 - [c126]Karthik Somayaji N. S., Hanbin Hu
, Peng Li:
Prioritized Reinforcement Learning for Analog Circuit Optimization With Design Knowledge. DAC 2021: 1231-1236 - [c125]Yukun Yang, Wenrui Zhang, Peng Li:
Backpropagated Neighborhood Aggregation for Accurate Training of Spiking Neural Networks. ICML 2021: 11852-11862 - [c124]Richard Boone, Wenrui Zhang
, Peng Li:
Efficient Biologically-Plausible Training of Spiking Neural Networks with Precise Timing. ICONS 2021: 2:1-2:8 - [c123]Jeong-Jun Lee, Jianhao Chen, Wenrui Zhang
, Peng Li:
Systolic-Array Spiking Neural Accelerators with Dynamic Heterogeneous Voltage Regulation. IJCNN 2021: 1-7 - [c122]Wenrui Zhang
, Peng Li:
Spiking Neural Networks with Laterally-Inhibited Self-Recurrent Units. IJCNN 2021: 1-8 - [c121]Hanbin Hu
, Chen He
, Peng Li:
Semi-supervised Wafer Map Pattern Recognition using Domain-Specific Data Augmentation and Contrastive Learning. ITC 2021: 113-122 - [i16]Yukun Yang, Wenrui Zhang, Peng Li:
Backpropagated Neighborhood Aggregation for Accurate Training of Spiking Neural Networks. CoRR abs/2107.06861 (2021) - [i15]Ling Liang, Zheng Qu, Zhaodong Chen, Fengbin Tu, Yujie Wu, Lei Deng, Guoqi Li, Peng Li, Yuan Xie:
H2Learn: High-Efficiency Learning Accelerator for High-Accuracy Spiking Neural Networks. CoRR abs/2107.11746 (2021) - [i14]Wenrui Zhang
, Peng Li:
Composing Recurrent Spiking Neural Networks using Locally-Recurrent Motifs and Risk-Mitigating Architectural Optimization. CoRR abs/2108.01793 (2021) - 2020
- [j70]Bo Sun, Shiping Wen, Shengbo Wang
, Tingwen Huang
, Yiran Chen, Peng Li:
Quantized synchronization of memristive neural networks with time-varying delays via super-twisting algorithm. Neurocomputing 380: 133-140 (2020) - [j69]Shiqin Wang
, Yuting Cao, Tingwen Huang
, Yiran Chen, Peng Li, Shiping Wen:
Sliding mode control of neural networks via continuous or periodic sampling event-triggering algorithm. Neural Networks 121: 140-147 (2020) - [j68]Lei Deng
, Yujie Wu, Xing Hu, Ling Liang
, Yufei Ding, Guoqi Li, Guangshe Zhao, Peng Li, Yuan Xie:
Rethinking the performance comparison between SNNS and ANNS. Neural Networks 121: 294-307 (2020) - [j67]You Zhao, Xing He, Tingwen Huang
, Junjian Huang, Peng Li
:
A smoothing neural network for minimization l1-lp in sparse signal reconstruction with measurement noises. Neural Networks 122: 40-53 (2020) - [j66]Joseph Riad
, Peng Li, Edgar Sánchez-Sinencio:
A Stabilizing Centralized Controller for On-Chip Power Delivery Networks. IEEE Trans. Circuits Syst. II Express Briefs 67-II(4): 680-684 (2020) - [c120]Jeong-Jun Lee, Peng Li:
Reconfigurable Dataflow Optimization for Spatiotemporal Spiking Neural Computation on Systolic Array Accelerators. ICCD 2020: 57-64 - [c119]Jianhao Chen, Joseph Riad, Edgar Sánchez-Sinencio, Peng Li:
Dynamic Heterogeneous Voltage Regulation for Systolic Array-Based DNN Accelerators. ICCD 2020: 486-493 - [c118]Joseph Riad, Jianhao Chen, Edgar Sánchez-Sinencio, Peng Li:
Variation-Aware Heterogeneous Voltage Regulation for Multi-Core Systems-on-a-Chip with On-Chip Machine Learning. ISQED 2020: 190-194 - [c117]Yu Wang, Jeong-Jun Lee, Yu Ding, Peng Li:
A Scalable FPGA Engine for Parallel Acceleration of Singular Value Decomposition. ISQED 2020: 370-376 - [c116]Hanbin Hu
, Nguyen Nguyen, Chen He
, Peng Li:
Advanced Outlier Detection Using Unsupervised Learning for Screening Potential Customer Returns. ITC 2020: 1-10 - [c115]Wenrui Zhang, Peng Li:
Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks. NeurIPS 2020 - [i13]Ling Liang, Xing Hu, Lei Deng, Yujie Wu, Guoqi Li, Yufei Ding, Peng Li, Yuan Xie:
Exploring Adversarial Attack in Spiking Neural Networks with Spike-Compatible Gradient. CoRR abs/2001.01587 (2020) - [i12]Wenrui Zhang, Peng Li:
Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks. CoRR abs/2002.10085 (2020) - [i11]Wenrui Zhang, Peng Li:
Skip-Connected Self-Recurrent Spiking Neural Networks with Joint Intrinsic Parameter and Synaptic Weight Training. CoRR abs/2010.12691 (2020)
2010 – 2019
- 2019
- [j65]Yu Liu
, Wenrui Zhang
, Peng Li:
Enabling Non-Hebbian Learning in Recurrent Spiking Neural Processors With Hardware-Friendly On-Chip Intrinsic Plasticity. IEEE J. Emerg. Sel. Topics Circuits Syst. 9(3): 465-474 (2019) - [j64]Yu Liu, Sai Sourabh Yenamachintala, Peng Li:
Energy-efficient FPGA Spiking Neural Accelerators with Supervised and Unsupervised Spike-timing-dependent-Plasticity. ACM J. Emerg. Technol. Comput. Syst. 15(3): 27:1-27:19 (2019) - [j63]Xin Zhan
, Peng Li, Edgar Sánchez-Sinencio:
Taming the Stability-Constrained Performance Optimization Challenge of Distributed On-Chip Voltage Regulation. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38(8): 1571-1584 (2019) - [j62]Xin Zhan
, Jianhao Chen
, Edgar Sánchez-Sinencio, Peng Li:
Power Management for Multicore Processors via Heterogeneous Voltage Regulation and Machine Learning Enabled Adaptation. IEEE Trans. Very Large Scale Integr. Syst. 27(11): 2641-2654 (2019) - [c114]Hanbin Hu
, Peng Li, Jianhua Z. Huang:
Enabling High-Dimensional Bayesian Optimization for Efficient Failure Detection of Analog and Mixed-Signal Circuits. DAC 2019: 17 - [c113]Wenrui Zhang
, Peng Li:
Spike-Train Level Backpropagation for Training Deep Recurrent Spiking Neural Networks. NeurIPS 2019: 7800-7811 - [i10]Chenye Zhao, Myung Seok Shim, Yang Li, Xuchong Zhang, Peng Li:
Deep Neural Networks with Auxiliary-Model Regulated Gating for Resilient Multi-Modal Sensor Fusion. CoRR abs/1901.10610 (2019) - [i9]Hanbin Hu
, Mit Shah, Jianhua Z. Huang, Peng Li:
Global Adversarial Attacks for Assessing Deep Learning Robustness. CoRR abs/1906.07920 (2019) - [i8]Wenrui Zhang, Peng Li:
Spike-Train Level Backpropagation for Training Deep Recurrent Spiking Neural Networks. CoRR abs/1908.06378 (2019) - [i7]Changqing Xu, Wenrui Zhang, Yu Liu, Peng Li:
Boosting Throughput and Efficiency of Hardware Spiking Neural Accelerators using Time Compression Supporting Multiple Spike Codes. CoRR abs/1909.04757 (2019) - [i6]Lei Deng, Yujie Wu, Yifan Hu, Ling Liang, Guoqi Li, Xing Hu, Yufei Ding, Peng Li, Yuan Xie:
Comprehensive SNN Compression Using ADMM Optimization and Activity Regularization. CoRR abs/1911.00822 (2019) - 2018
- [j61]Changqing Xu
, Yi Liu, Peng Li, Yintang Yang:
Unified multi-objective mapping for network-on-chip using genetic-based hyper-heuristic algorithms. IET Comput. Digit. Tech. 12(4): 158-166 (2018) - [j60]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) - [j59]Alexandre Y. Yamamoto, Kyle M. Sundqvist, Peng Li, H. Rusty Harris:
Simulation of a Multidimensional Input Quantum Perceptron. Quantum Inf. Process. 17(6): 128 (2018) - [j58]Xin Zhan
, Joseph Riad, Peng Li, Edgar Sánchez-Sinencio:
Design Space Exploration of Distributed On-Chip Voltage Regulation Under Stability Constraint. IEEE Trans. Very Large Scale Integr. Syst. 26(8): 1580-1584 (2018) - [c112]Hanbin Hu
, Qingran Zheng, Ya Wang, Peng Li:
HFMV: hybridizing formal methods and machine learning for verification of analog and mixed-signal circuits. DAC 2018: 95:1-95:6 - [c111]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 - [c110]Hanbin Hu
, Peng Li, Jianhua Z. Huang:
Parallelizable Bayesian optimization for analog and mixed-signal rare failure detection with high coverage. ICCAD 2018: 98 - [c109]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 - [c108]Yingyezhe Jin, Wenrui Zhang
, Peng Li:
Hybrid Macro/Micro Level Backpropagation for Training Deep Spiking Neural Networks. NeurIPS 2018: 7005-7015 - [i5]Yingyezhe Jin, Peng Li, Wenrui Zhang:
Hybrid Macro/Micro Level Backpropagation for Training Deep Spiking Neural Networks. CoRR abs/1805.07866 (2018) - [i4]Ting-Jui Chang, Yukun He, Peng Li:
Efficient Two-Step Adversarial Defense for Deep Neural Networks. CoRR abs/1810.03739 (2018) - [i3]Myung Seok Shim, Peng Li:
Optimized Gated Deep Learning Architectures for Sensor Fusion. CoRR abs/1810.04160 (2018) - 2017
- [j57]Qian Wang, Youjie Li, Botang Shao, Siddhartha Dey, Peng Li:
Energy efficient parallel neuromorphic architectures with approximate arithmetic on FPGA. Neurocomputing 221: 146-158 (2017) - [j56]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) - [j55]Ya Wang, Di Gao, Dani A. Tannir, Ning Dong, G. Peter Fang, Wei Dong, Peng Li:
Multiharmonic Small-Signal Modeling of Low-Power PWM DC-DC Converters. ACM Trans. Design Autom. Electr. Syst. 22(4): 68:1-68:16 (2017) - [c107]Ya Wang, Wenrui Zhang, Peng Li, Jian Gong:
Convergence-Boosted Graph Partitioning using Maximum Spanning Trees for Iterative Solution of Large Linear Circuits. DAC 2017: 69:1-69:6 - [c106]Ang Li, Peng Li, Tingwen Huang, Edgar Sánchez-Sinencio:
Noise-sensitive feedback loop identification in linear time-varying analog circuits. DATE 2017: 1285-1288 - [c105]Honghuang Lin, Asad M. Khan, Peng Li:
Statistical circuit performance dependency analysis via sparse relevance kernel machine. ICICDT 2017: 1-4 - [c104]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 - [c103]Amarnath Mahadevuni, Peng Li:
Navigating mobile robots to target in near shortest time using reinforcement learning with spiking neural networks. IJCNN 2017: 2243-2250 - [c102]Myung Seok Shim, Peng Li:
Biologically inspired reinforcement learning for mobile robot collision avoidance. IJCNN 2017: 3098-3105 - [c101]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
- [j54]Parijat Mukherjee
, Peng Li:
Using Presilicon Knowledge to Excite Nonlinear Failure Modes in Large Mixed-Signal Circuits. IEEE Des. Test 33(5): 28-34 (2016) - [j53]Qian Wang, Yongtae Kim, Peng Li:
Neuromorphic Processors with Memristive Synapses: Synaptic Interface and Architectural Exploration. ACM J. Emerg. Technol. Comput. Syst. 12(4): 35:1-35:22 (2016) - [j52]Ya Wang
, Peng Li, Suming Lai:
Robust and Efficient Transistor-Level Envelope-Following Analysis of PWM/PFM/PSM DC-DC Converters. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 35(11): 1836-1847 (2016) - [j51]Dani A. Tannir, Ya Wang, Peng Li:
Accurate Modeling of Nonideal Low-Power PWM DC-DC Converters Operating in CCM and DCM using Enhanced Circuit-Averaging Techniques. ACM Trans. Design Autom. Electr. Syst. 21(4): 61:1-61:15 (2016) - [c100]Honghuang Lin, Peng Li:
Relevance vector and feature machine for statistical analog circuit characterization and built-in self-test optimization. DAC 2016: 11:1-11:6 - [c99]Xin Zhan, Peng Li, Edgar Sánchez-Sinencio:
Distributed on-chip regulation: theoretical stability foundation, over-design reduction and performance optimization. DAC 2016: 54:1-54:6 - [c98]Ya Wang, Di Gao, Dani A. Tannir, Peng Li:
Multi-harmonic nonlinear modeling of low-power PWM DC-DC converters operating in CCM and DCM. DATE 2016: 409-414 - [c97]Qian Wang, Peng Li:
D-LSM: Deep Liquid State Machine with unsupervised recurrent reservoir tuning. ICPR 2016: 2652-2657 - [c96]Yingyezhe Jin, Peng Li:
AP-STDP: A novel self-organizing mechanism for efficient reservoir computing. IJCNN 2016: 1158-1165 - [c95]Qian Wang, Youjie Li, Peng Li:
Liquid state machine based pattern recognition on FPGA with firing-activity dependent power gating and approximate computing. ISCAS 2016: 361-364 - [c94]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
- [j50]Peng Li:
The Art of Certifying Analog/Mixed-Signal Circuits. IEEE Des. Test 32(1): 79-80 (2015) - [j49]Yongtae Kim, Yong Zhang, Peng Li:
A Reconfigurable Digital Neuromorphic Processor with Memristive Synaptic Crossbar for Cognitive Computing. ACM J. Emerg. Technol. Comput. Syst. 11(4): 38:1-38:25 (2015) - [j48]Shiping Wen, Tingwen Huang
, Zhigang Zeng
, Yiran Chen, Peng Li:
Circuit design and exponential stabilization of memristive neural networks. Neural Networks 63: 48-56 (2015) - [j47]Honghuang Lin, Peng Li:
Circuit Performance Classification With Active Learning Guided Sampling for Support Vector Machines. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 34(9): 1467-1480 (2015) - [j46]Botang Shao, Peng Li:
Array-Based Approximate Arithmetic Computing: A General Model and Applications to Multiplier and Squarer Design. IEEE Trans. Circuits Syst. I Regul. Pap. 62-I(4): 1081-1090 (2015) - [j45]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) - [j44]Tong Xu, Peng Li, Savithri Sundareswaran:
Decoupling Capacitance Design Strategies for Power Delivery Networks with Power Gating. ACM Trans. Design Autom. Electr. Syst. 20(3): 38:1-38:30 (2015) - [j43]Qian Wang
, Peng Li, Yongtae Kim:
A Parallel Digital VLSI Architecture for Integrated Support Vector Machine Training and Classification. IEEE Trans. Very Large Scale Integr. Syst. 23(8): 1471-1484 (2015) - [j42]Yongtae Kim, Yong Zhang, Peng Li:
Energy Efficient Approximate Arithmetic for Error Resilient Neuromorphic Computing. IEEE Trans. Very Large Scale Integr. Syst. 23(11): 2733-2737 (2015) - [c93]Qian Wang, Yingyezhe Jin, Peng Li:
General-purpose LSM learning processor architecture and theoretically guided design space exploration. BioCAS 2015: 1-4 - [c92]Shuangchen Li, Ang Li, Yuan Zhe, Yongpan Liu, Peng Li, Guangyu Sun, Yu Wang, Huazhong Yang, Yuan Xie:
Leveraging emerging nonvolatile memory in high-level synthesis with loop transformations. ISLPED 2015: 61-66 - [c91]Andrew N. Fisher, Chris J. Myers
, Peng Li:
Reachability Analysis Using Extremal Rates. NFM 2015: 158-172 - 2014
- [j41]