Interpretable Complex-Valued Neural Networks for Privacy Protection
Xiang, etc. (2020). "Interpretable Complex-Valued Neural Networks for Privacy Protection" ICLR 2020.
CV
Education
- B.S. in GitHub, GitHub University, 2012
- M.S. in Jekyll, GitHub University, 2014
- Ph.D in Version Control Theory, GitHub University, 2018 (expected)
Work experience
- Summer 2015: Research Assistant
- Github University
- Duties included: Tagging issues
- Supervisor: Professor Git
- Fall 2015: Research Assistant
- Github University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
Skills
- Skill 1
- Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
- Skill 3
Publications
Interpreting Multivariate Shapley Interactions in DNNs
Zhang, etc. (2021). "Interpreting Multivariate Shapley Interactions in DNNs" AAAI 2021.
Interpreting and Boosting Dropout from a Game-Theoretic View
Zhang, etc. (2021). "Interpreting and Boosting Dropout from a Game-Theoretic View" ICLR 2021.
Discovering and Explaining the Representation Bottleneck of DNNs
Deng, etc. (2022). "Discovering and Explaining the Representation Bottleneck of DNNs" ICLR 2022.
Quantification and Analysis of Layer-wise and Pixel-wise Information Discarding
Ma, etc. (2022). "Quantification and Analysis of Layer-wise and Pixel-wise Information Discarding" ICML 2022.
Talks
Talk 1 on Relevant Topic in Your Field
Talk at UC San Francisco, Department of Testing, San Francisco, California
Tutorial 1 on Relevant Topic in Your Field
Tutorial at UC-Berkeley Institute for Testing Science, Berkeley CA, USA
Talk 2 on Relevant Topic in Your Field
Talk at London School of Testing, London, UK
Conference Proceeding talk 3 on Relevant Topic in Your Field
Conference proceedings talk at Testing Institute of America 2014 Annual Conference, Los Angeles, CA
Teaching
Service and leadership
- Currently signed in to 43 different slack teams