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2020 – today
- 2023
[b1]Ximing Qiao:
Toward Trustworthy Machine Learning with Blackbox and Whitebox Methods. Duke University, Durham, NC, USA, 2023- [c4]Yanchun Shen
, Ximing Qiao, Zhiwang Zhong, Hongyu Sheng:
Study on the Characteristics of Liquid Crystal-based Terahertz Metadevices in Wireless Communication Circuits. AISNS 2023: 135-140 - [c3]Ximing Qiao, Hai Li:
On a New Type of Neural Computation for Probabilistic Symbolic Reasoning. IJCNN 2023: 1-9 - 2022
- [i3]Ximing Qiao, Hai Li:
Learning and Compositionality: a Unification Attempt via Connectionist Probabilistic Programming. CoRR abs/2208.12789 (2022) - 2021
- [i2]Ximing Qiao, Yuhua Bai, Siping Hu, Ang Li, Yiran Chen, Hai Li:
On Provable Backdoor Defense in Collaborative Learning. CoRR abs/2101.08177 (2021)
2010 – 2019
- 2019
- [j2]Bonan Yan, Bing Li, Ximing Qiao, Cheng-Xin Xue, Meng-Fan Chang, Yiran Chen, Hai Helen Li:
Resistive Memory-Based In-Memory Computing: From Device and Large-Scale Integration System Perspectives. Adv. Intell. Syst. 1(7): 1900068 (2019) - [j1]Chaofei Yang, Ximing Qiao, Yiran Chen:
Neuromorphic Computing Systems: From CMOS To Emerging Nonvolatile Memory. IPSJ Trans. Syst. LSI Des. Methodol. 12: 53-64 (2019) - [c2]Ximing Qiao, Yukun Yang, Hai Li:
Defending Neural Backdoors via Generative Distribution Modeling. NeurIPS 2019: 14004-14013 - [i1]Ximing Qiao, Yukun Yang, Hai Li:
Defending Neural Backdoors via Generative Distribution Modeling. CoRR abs/1910.04749 (2019) - 2018
- [c1]Ximing Qiao, Xiong Cao, Huanrui Yang, Linghao Song, Hai Li:
Atomlayer: a universal reRAM-based CNN accelerator with atomic layer computation. DAC 2018: 103:1-103:6
Coauthor Index
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