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ORCIDKe Wang 0035
Person information
- affiliation: University of California Santa Barbara, Department of Statistics and Applied Probability, CA, USA
Other persons with the same name
- Ke Wang — disambiguation page
- Ke Wang 0001
![[0000-0002-8021-4951]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-8021-4951")
— Simon Fraser University, Burnaby, BC, Canada (and 1 more) - Ke Wang 0002 — Harbin Institute of Technology, Department of Mathematics, Weihai, China (and 1 more)
- Ke Wang 0003 — Hong Kong University of Science and Technology, Jockey Club Institute for Advanced Study, Hong Kong (and 2 more)
- Ke Wang 0004 — Shanghai University, School of Management, China (and 1 more)
- Ke Wang 0005 — Beijing University of Technology, College of Electronic and Control Engineering, China (and 2 more)
- Ke Wang 0006 — National University of Singapore, NUS Graduate School for Integrative Sciences and Engineering, Singapore
- Ke Wang 0007 — RMIT University, School of Engineering, Melbourne, Australia (and 1 more)
- Ke Wang 0008 — Chang'an University, School of Highway, Xi'an, China
- Ke Wang 0009 — Columbia University, New York, NY, USA
- Ke Wang 0010 — PLA University of Science and Technology, Department of Satellite Communications, Nanjing, China
- Ke Wang 0011 — University of Virginia, Department of Computer Science, Charlottesville, VA, USA
- Ke Wang 0012 — Intel (and 1 more)
- Ke Wang 0013 — Beijing University of Posts and Telecommunications, School of Information and Communication Engineering / MoE Key Laboratory of Universal Wireless Communications, China
- Ke Wang 0014 — Chinese Academy of Sciences, Institute of Electrical Engineering, Key Laboratory of Power Electronics and Electric Drive, Beijing, China
- Ke Wang 0015 — China Electric Power Research Institute, Electric Automation Department, Nanjing, China
- Ke Wang 0016 — Zhejiang University, Institute of Remote Sensing and Information System Application / College of Environmental and Resource Sciences, Hangzhou, China
- Ke Wang 0017 — Chongqing University, State Key Laboratory of Mechanical Transmission, China
- Ke Wang 0018 — Xian University of Architecture and Technology, School of Management, China
- Ke Wang 0019 — Nanjing University of Aeronautics and Astronautics, School of Electronic and Information Engineering, China
- Ke Wang 0020 — University of Glasgow, School of Engineering, UK
- Ke Wang 0021 — University of North Carolina, Department of Computer Science, Chapel Hill, NC, USA
- Ke Wang 0023 — China University of Geosciences, Wuhan, China (and 1 more)
- Ke Wang 0024 — Chongqing University, College of Computer Science, China
- Ke Wang 0025 — Zhejiang University of Technology, College of Information Engineering, China
- Ke Wang 0026 — Shanghai University, School of Mechatronic Engineering and Automation, China
- Ke Wang 0027 — Shandong University of Science and Technology, College of Geomatics, Qingdao, China
- Ke Wang 0028 — Harbin Institute of Technology, State Key Laboratory of Robotics and System, Harbin, China
- Ke Wang 0029 — Harbin Institute of Technology, Instrument Science and Technology, China
- Ke Wang 0030 — George Washington University, Department of Electrical and Computer Engineering, Washington, DC, USA
- Ke Wang 0031 — Sichuan University, College of Mathematics, Chengdu, China
- Ke Wang 0032 — Hohai University, State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing, China
- Ke Wang 0033 — Tsinghua University, Department of Electronic Engineering, Beijing, China
- Ke Wang 0034 — Zhejiang University, Institute of VLSI Design, China
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Journal Articles
- 2023
[j3]Ke Wang, Alexander Franks, Sang-Yun Oh:
Learning Gaussian graphical models with latent confounders. J. Multivar. Anal. 198: 105213 (2023)- [j2]Ke Wang, Vidya Muthukumar, Christos Thrampoulidis:
Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation. IEEE Trans. Inf. Theory 69(12): 7909-7952 (2023) - 2022
- [j1]Ke Wang, Christos Thrampoulidis:
Binary Classification of Gaussian Mixtures: Abundance of Support Vectors, Benign Overfitting, and Regularization. SIAM J. Math. Data Sci. 4(1): 260-284 (2022)
Conference and Workshop Papers
- 2022
- [c3]Tina Behnia, Ke Wang, Christos Thrampoulidis:
On how to avoid exacerbating spurious correlations when models are overparameterized. ISIT 2022: 121-126 - 2021
- [c2]Ke Wang, Christos Thrampoulidis:
Benign Overfitting in Binary Classification of Gaussian Mixtures. ICASSP 2021: 4030-4034 - [c1]Ke Wang, Vidya Muthukumar, Christos Thrampoulidis:
Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation. NeurIPS 2021: 24164-24179
Informal and Other Publications
- 2022
- [i3]Tina Behnia, Ke Wang, Christos Thrampoulidis:
On how to avoid exacerbating spurious correlations when models are overparameterized. CoRR abs/2206.12739 (2022) - 2021
- [i2]Ke Wang, Vidya Muthukumar, Christos Thrampoulidis:
Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation. CoRR abs/2106.10865 (2021) - 2020
- [i1]Ke Wang, Christos Thrampoulidis:
Benign Overfitting in Binary Classification of Gaussian Mixtures. CoRR abs/2011.09148 (2020)
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