Lin Chen is a postdoctoral scholar at the Simons Institute for the Theory of Computing, University of California, Berkeley . His research interests focus on machine learning theory.
News
- My paper Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS was accepted to ICLR 2021. slides
Selected Awards
- Google Ph.D. Fellowship, 2018
- Google Excellence Scholarship, 2013
- National Scholarship, 2011
Selected Publications
* denotes alphabetical order or equal contribution.
- Lin Chen, Sheng Xu, Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS, ICLR 2021. slides
- Lin Chen, Yifei Min, Mikhail Belkin, Amin Karbasi, Multiple Descent: Design Your Own Generalization Curve.
- Lin Chen*, Qian Yu*, Hannah Lawrence, Amin Karbasi, Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition, NeurIPS 2020.
- Lin Chen*, Moran Feldman*, and Amin Karbasi*, Unconstrained Submodular Maximization with Constant Adaptive Complexity, STOC 2019.