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2020 – today
- 2024
[j3]Dingbang Liu
, Fenghui Ren, Jun Yan, Guoxin Su, Wen Gu, Shohei Kato:
Scaling Up Multi-Agent Reinforcement Learning: An Extensive Survey on Scalability Issues. IEEE Access 12: 94610-94631 (2024)- 2023
- [c4]Haoxiang Zhou, Haiqiao Hong, Dingbang Liu, Hang Liu, Yu Xia, Kai Li, Jun Liu, Shaobo Luo, Wei Mao, Hao Yu:
RISC-V based Fully-Parallel SRAM Computing-in-Memory Accelerator with High Hardware Utilization and Data Reuse Rate. AICAS 2023: 1-5 - [c3]Qi Chen, Hao Hu, Cai Deng, Dingbang Liu, Shiyi Li, Bo Tang, Ting Yao, Wen Xia:
EEPH: An Efficient Extendible Perfect Hashing for Hybrid PMem-DRAM. ICDE 2023: 1366-1378 - 2022
- [j2]Dingbang Liu, Haoxiang Zhou, Wei Mao, Jun Liu, Yuliang Han, Changhai Man, Qiuping Wu, Zhiru Guo, Mingqiang Huang, Shaobo Luo, Mingsong Lv, Quan Chen, Hao Yu:
An Energy-Efficient Mixed-Bit CNN Accelerator With Column Parallel Readout for ReRAM-Based In-Memory Computing. IEEE J. Emerg. Sel. Topics Circuits Syst. 12(4): 821-834 (2022) - [c2]Dingbang Liu, Wei Mao, Haoxiang Zhou, Jun Liu, Qiuping Wu, Haiqiao Hong, Hao Yu:
An Energy-Efficient Mixed-Bit ReRAM-based Computing-in-Memory CNN Accelerator with Fully Parallel Readout. APCCAS 2022: 1-5 - 2021
- [j1]Dingbang Liu, Hao Yu, Yang Chai:
Low-Power Computing with Neuromorphic Engineering. Adv. Intell. Syst. 3(2): 2000150 (2021) - 2020
- [c1]Wei Mao, Zhihua Xiao, Peng Xu, Hongwei Ren, Dingbang Liu, Shirui Zhao, Fengwei An, Hao Yu:
Energy-Efficient Machine Learning Accelerator for Binary Neural Networks. ACM Great Lakes Symposium on VLSI 2020: 77-82
Coauthor Index
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