Arsen Vasilyan

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 22

Top Topics

Monotone Boolean Functions

Noise Sensitivity

Covariate Shift

Top Venues

Publications

Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
Testable Learning with Distribution Shift. COLT (2024)
Gautam Chandrasekaran, Adam R. Klivans, Vasilis Kontonis, Konstantinos Stavropoulos, Arsen Vasilyan
Efficient Discrepancy Testing for Learning with Distribution Shift. CoRR (2024)
Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds. CoRR (2024)
Ilan Reuven Cohen, Alon Eden, Talya Eden, Arsen Vasilyan
Plant-and-Steal: Truthful Fair Allocations via Predictions. CoRR (2024)
Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds. COLT (2024)
Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
An Efficient Tester-Learner for Halfspaces. ICLR (2024)
Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan
Tolerant Algorithms for Learning with Arbitrary Covariate Shift. CoRR (2024)
Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
Tester-Learners for Halfspaces: Universal Algorithms. NeurIPS (2023)
Jane Lange, Ephraim Linder, Sofya Raskhodnikova, Arsen Vasilyan
Local Lipschitz Filters for Bounded-Range Functions. CoRR (2023)
Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
Tester-Learners for Halfspaces: Universal Algorithms. CoRR (2023)
Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
Testable Learning with Distribution Shift. CoRR (2023)
Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
An Efficient Tester-Learner for Halfspaces. CoRR (2023)
Ronitt Rubinfeld, Arsen Vasilyan
Testing Distributional Assumptions of Learning Algorithms. STOC (2023)
Jane Lange, Arsen Vasilyan
Agnostic proper learning of monotone functions: beyond the black-box correction barrier. CoRR (2023)
Jane Lange, Arsen Vasilyan
Agnostic proper learning of monotone functions: beyond the black-box correction barrier. FOCS (2023)
Jane Lange, Ronitt Rubinfeld, Arsen Vasilyan
Properly learning monotone functions via local reconstruction. CoRR (2022)
Ronitt Rubinfeld, Arsen Vasilyan
Testing distributional assumptions of learning algorithms. CoRR (2022)
Jane Lange, Ronitt Rubinfeld, Arsen Vasilyan
Properly learning monotone functions via local correction. FOCS (2022)
Ronitt Rubinfeld, Arsen Vasilyan
Monotone probability distributions over the Boolean cube can be learned with sublinear samples. CoRR (2020)
Ronitt Rubinfeld, Arsen Vasilyan
Monotone Probability Distributions over the Boolean Cube Can Be Learned with Sublinear Samples. ITCS (2020)
Ronitt Rubinfeld, Arsen Vasilyan
Approximating the Noise Sensitivity of a Monotone Boolean Function. APPROX-RANDOM (2019)
Ronitt Rubinfeld, Arsen Vasilyan
Approximating the noise sensitivity of a monotone Boolean function. CoRR (2019)