Scholar
Arsen Vasilyan
Google Scholar ID: hLseRm8AAAAJ
UT Austin
Citations & Impact
Citations
162
H-index
8
i10-index
6
Publications
20
Co-authors
0
Contact
Publications
Resume
Academic Achievements
- - Publications:
- - "The Power of Iterative Filtering for Supervised Learning with (Heavy) Contamination", NeurIPS 2025
- - "Robust learning of halfspaces under log-concave marginals", NeurIPS 2025
- - "Learning Constant-Depth Circuits in Malicious Noise Models", COLT 2025
- - "Local Lipschitz Filters for Bounded-Range Functions", SODA 2025
- - "Tolerant Algorithms for Learning with Arbitrary Covariate Shift", NeurIPS 2024
- - "Efficient Discrepancy Testing for Learning with Distribution Shift", NeurIPS 2024
- - "Plant-and-Steal: Truthful Fair Allocations via Predictions", NeurIPS 2024
- - "Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds", COLT 2024
- - "Testable Learning with Distribution Shift", COLT 2024
- - "An Efficient Tester-Learner for Halfspaces", ICLR 2024
- - "Tester-Learners for Halfspaces: Universal Algorithms", NeurIPS 2023
- - "Agnostic Proper Learning of Monotone Functions: Beyond the Black-box Correction Barrier", FOCS 2023
- - "Testing Distributional Assumptions of Learning Algorithms", STOC 2023
- - "Properly Learning Monotone Functions via Local Reconstruction", FOCS 2022
- - "Monotone Probability Distributions over the Boolean Cube Can Be Learned with Sublinear Samples", incomplete information
Research Experience
- - Postdoctoral Fellow: Institute for Foundations of Machine Learning (UT Austin)
- - Research Fellow: The Simons Institute for the Theory of Computing
Education
- - PhD: Massachusetts Institute of Technology, advised by Jonathan Kelner and Ronitt Rubinfeld
- - Undergraduate: Massachusetts Institute of Technology, major in Computer Science, double minor in Physics and Philosophy
Background
- - Research interests: Computational learning theory, computational statistics, distribution learning and testing
- - Professional field: Computer Science
- - Brief introduction: Currently a postdoctoral fellow at the Institute for Foundations of Machine Learning (UT Austin). Previously, a research fellow at The Simons Institute for the Theory of Computing.
Miscellany
- - Personal interests: Competed in the International Physics Olympiad (IPhO)