| 2026 | COLT | Testing Noise Assumptions of Learning Algorithms. | Surbhi Goel, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan |
| 2026 | COLT | Sandwiching Polynomials for Geometric Concepts with Low Intrinsic Dimension. | Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan |
| 2026 | COLT | Equivalence of Coarse and Fine-Grained Models for Learning with Distribution Shift. | Shyamal Patel, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan |
| 2026 | STOC | A Fully Polynomial-Time Algorithm for Robustly Learning Halfspaces over the Hypercube. | Gautam Chandrasekaran, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan |
| 2025 | COLT | Learning Constant-Depth Circuits in Malicious Noise Models. | Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan |
| 2025 | SODA | Local Lipschitz Filters for Bounded-Range Functions with Applications to Arbitrary Real-Valued Functions. | Jane Lange, Ephraim Linder, Sofya Raskhodnikova, Arsen Vasilyan |
| 2024 | COLT | Testable Learning with Distribution Shift. | Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan |
| 2024 | COLT | Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds. | Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan |
| 2024 | ICLR | An Efficient Tester-Learner for Halfspaces. | Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan |
| 2023 | FOCS | Agnostic proper learning of monotone functions: beyond the black-box correction barrier. | Jane Lange, Arsen Vasilyan |
| 2023 | STOC | Testing Distributional Assumptions of Learning Algorithms. | Ronitt Rubinfeld, Arsen Vasilyan |
| 2022 | FOCS | Properly learning monotone functions via local correction. | Jane Lange, Ronitt Rubinfeld, Arsen Vasilyan |