Arsen Vasilyan

35 papers A* 12A 2Journal 20Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Sandwiching Polynomials for Geometric Concepts with Low Intrinsic Dimension. CoRR Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2026	A	`conf`	Testable Algorithms for Approximately Counting Edges and Triangles in Sublinear Time and Space. ITCS Talya Eden, Ronitt Rubinfeld, Arsen Vasilyan
2025	J	`jnl`	A Fully Polynomial-Time Algorithm for Robustly Learning Halfspaces over the Hypercube. CoRR Gautam Chandrasekaran, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2025	A*	`conf`	Learning Constant-Depth Circuits in Malicious Noise Models. COLT Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2025	A*	`conf`	Local Lipschitz Filters for Bounded-Range Functions with Applications to Arbitrary Real-Valued Functions. SODA Jane Lange, Ephraim Linder, Sofya Raskhodnikova, Arsen Vasilyan
2025	J	`jnl`	Robust learning of halfspaces under log-concave marginals. CoRR Jane Lange, Arsen Vasilyan
2025	J	`jnl`	Testable algorithms for approximately counting edges and triangles in sublinear time and space. CoRR Talya Eden, Ronitt Rubinfeld, Arsen Vasilyan
2025	J	`jnl`	Testing Noise Assumptions of Learning Algorithms. CoRR Surbhi Goel, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2025	J	`jnl`	The Power of Iterative Filtering for Supervised Learning with (Heavy) Contamination. CoRR Adam R. Klivans, Konstantinos Stavropoulos, Kevin Tian, Arsen Vasilyan
2024	A*	`conf`	An Efficient Tester-Learner for Halfspaces. ICLR Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2024	A*	`conf`	Efficient Discrepancy Testing for Learning with Distribution Shift. NeurIPS Gautam Chandrasekaran, Adam R. Klivans, Vasilis Kontonis, Konstantinos Stavropoulos, Arsen Vasilyan
2024	J	`jnl`	Efficient Discrepancy Testing for Learning with Distribution Shift. CoRR Gautam Chandrasekaran, Adam R. Klivans, Vasilis Kontonis, Konstantinos Stavropoulos, Arsen Vasilyan
2024	J	`jnl`	Learning Constant-Depth Circuits in Malicious Noise Models. CoRR Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2024	A*	`conf`	Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds. COLT Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2024	J	`jnl`	Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds. CoRR Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2024	A*	`conf`	Plant-and-Steal: Truthful Fair Allocations via Predictions. NeurIPS Ilan Reuven Cohen, Alon Eden, Talya Eden, Arsen Vasilyan
2024	J	`jnl`	Plant-and-Steal: Truthful Fair Allocations via Predictions. CoRR Ilan Reuven Cohen, Alon Eden, Talya Eden, Arsen Vasilyan
2024	A*	`conf`	Testable Learning with Distribution Shift. COLT Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2024	A*	`conf`	Tolerant Algorithms for Learning with Arbitrary Covariate Shift. NeurIPS Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan
2024	J	`jnl`	Tolerant Algorithms for Learning with Arbitrary Covariate Shift. CoRR Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan
2023	A*	`conf`	Agnostic proper learning of monotone functions: beyond the black-box correction barrier. FOCS Jane Lange, Arsen Vasilyan
2023	J	`jnl`	Agnostic proper learning of monotone functions: beyond the black-box correction barrier. CoRR Jane Lange, Arsen Vasilyan
2023	J	`jnl`	An Efficient Tester-Learner for Halfspaces. CoRR Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2023	J	`jnl`	Local Lipschitz Filters for Bounded-Range Functions. CoRR Jane Lange, Ephraim Linder, Sofya Raskhodnikova, Arsen Vasilyan
2023	J	`jnl`	Testable Learning with Distribution Shift. CoRR Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2023	A*	`conf`	Tester-Learners for Halfspaces: Universal Algorithms. NeurIPS Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2023	J	`jnl`	Tester-Learners for Halfspaces: Universal Algorithms. CoRR Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2023	A*	`conf`	Testing Distributional Assumptions of Learning Algorithms. STOC Ronitt Rubinfeld, Arsen Vasilyan
2022	A*	`conf`	Properly learning monotone functions via local correction. FOCS Jane Lange, Ronitt Rubinfeld, Arsen Vasilyan
2022	J	`jnl`	Properly learning monotone functions via local reconstruction. CoRR Jane Lange, Ronitt Rubinfeld, Arsen Vasilyan
2022	J	`jnl`	Testing distributional assumptions of learning algorithms. CoRR Ronitt Rubinfeld, Arsen Vasilyan
2020	A	`conf`	Monotone Probability Distributions over the Boolean Cube Can Be Learned with Sublinear Samples. ITCS Ronitt Rubinfeld, Arsen Vasilyan
2020	J	`jnl`	Monotone probability distributions over the Boolean cube can be learned with sublinear samples. CoRR Ronitt Rubinfeld, Arsen Vasilyan
2019	—	`conf`	Approximating the Noise Sensitivity of a Monotone Boolean Function. APPROX-RANDOM Ronitt Rubinfeld, Arsen Vasilyan
2019	J	`jnl`	Approximating the noise sensitivity of a monotone Boolean function. CoRR Ronitt Rubinfeld, Arsen Vasilyan