Sihan Liu's Personal Page
I am a second-year PhD student in UC San Diego's theoretical computer science group, where I am extremely fortuate to be advised by Daniel Kane.
I am interested in algorithmic and statistical problems related to the foundations of machine learning.
- In theory, there is no difference between theory and practice. But in practice, there is.
My music collection
- Sampling Equilibria: Fast No-Regret Learning in Structured Games (Daniel Beaglehole, Max Hopkins, Daniel Kane, Shachar Lovett)
- Develop a general framework of sampling equilibria from games of large state space.
- Fast algorithm for computing approximate equilibria for Colonel Blotto Game.
- Accept to SODA 2023. Link to Manuscript
- Nearly-Tight Bounds for Testing Histogram Distributions (C. Cannone, I. Diakonikolas, D. Kane)
- Computational-Statistical Gaps in Reinforcement Learning (D. Kane, S. Lovett, G. Mahajan)
- 2021.10 - 2022.2
- Accept to COLT 2022. Link
- Present the first computational lower bound for RL with linear function approximation.
- Convergence and Sample Complexity of SGD in GANs (C. Tzamos, V. Kontonis)
- 2020.1 - 2020.10
- Propose a theoretical framework for analyzing the performance of stochastic gradient ascent descent in non-convex general sum game.
- Obtain theoretical guarantees on nearly optimal sample complexity and convergence rate of Generative Adversarial Networks in learning one-layer non-linear neural nets.
- Selected to present at CS Student Research Symposium. Link to Manuscript
- Competitive Programming
- 2018 - Present
- Dieter van Melkebeek
- Achievements: 2019 ICPC North Central NA Regional Contest #3 over 183 teams (Team NP-Easiness), Codejam Round 2 Top 3% (leo990629), Hackercup Round 2 Top 10% (sihan.liu.3139).
- Software Enginner Intern in DataChat
- 2019.6 - Present
- DataChat Inc.
- Constrained Natural Language (CNL) parsing: intention inference and entity retrieval from structured natural language.
- Autocomplete Engine: provide data-sensitive suggestions in the middle of typing.
- Linter: semantic highlighting in user input.
- Skills used: React.js + Redux + Saga, Golang, Python, RedisStore, spaCy.
- Bachelor degrees in Computer Science and Mathematics (4.0/4.0)
- GPA: 4.0/4.0 Dewitt Undergraduate Scholarship
- Coursework: Learning Theory, Advanced Algorithm, Algorithmic Game Theory, Mechanism Design, Quantum Computing
- University of Wisconsin Madison
- 2017 - 2021
- Computational Learning Theory - Survey over learning linear threshold functions under Random/Adversarial/Massart noise model
- Mechanism Design - Survey on sample complexity of mechanism design
- Robust Statistics - GAN and Robust Statistics