Arsen Vasilyan

According to our database, Arsen Vasilyan authored at least 14 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Efficient Discrepancy Testing for Learning with Distribution Shift.

Gautam Chandrasekaran, Adam R. Klivans, Vasilis Kontonis, Konstantinos Stavropoulos, Arsen Vasilyan

CoRR, 2024

Plant-and-Steal: Truthful Fair Allocations via Predictions.

Ilan Reuven Cohen, Alon Eden, Talya Eden, Arsen Vasilyan

CoRR, 2024

Tolerant Algorithms for Learning with Arbitrary Covariate Shift.

Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan

CoRR, 2024

An Efficient Tester-Learner for Halfspaces.

Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds.

Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Testable Learning with Distribution Shift.

Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

Local Lipschitz Filters for Bounded-Range Functions.

Jane Lange, Ephraim Linder, Sofya Raskhodnikova, Arsen Vasilyan

CoRR, 2023

Testing Distributional Assumptions of Learning Algorithms.

Ronitt Rubinfeld, Arsen Vasilyan

Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023

Tester-Learners for Halfspaces: Universal Algorithms.

Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Agnostic proper learning of monotone functions: beyond the black-box correction barrier.

Jane Lange, Arsen Vasilyan

Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

2022

Properly learning monotone functions via local reconstruction.

Jane Lange, Ronitt Rubinfeld, Arsen Vasilyan

CoRR, 2022

Properly learning monotone functions via local correction.

Jane Lange, Ronitt Rubinfeld, Arsen Vasilyan

Proceedings of the 63rd IEEE Annual Symposium on Foundations of Computer Science, 2022

2020

Monotone Probability Distributions over the Boolean Cube Can Be Learned with Sublinear Samples.

Ronitt Rubinfeld, Arsen Vasilyan

Proceedings of the 11th Innovations in Theoretical Computer Science Conference, 2020

2019

Approximating the Noise Sensitivity of a Monotone Boolean Function.

Ronitt Rubinfeld, Arsen Vasilyan

Proceedings of the Approximation, 2019