Welcome!

I’m currently a PhD student in the Department of Computer Science at Massachusetts Institute of Technology, advised by Jonathan Kelner and Ronitt Rubinfeld. I am graduating in Spring 2024, and currently applying for postdocs. My scientific research interests include:

Computational learning theory
Distribution learning and testing
Computational statistics
Sublinear algorithms

Feel free to contact me via e-mail!

Publications:

An Efficient Tester-Learner for Halfspaces
Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
12th International Conference on Learning Representations (ICLR 2024), to appear.

Tester-Learners for Halfspaces: Universal Algorithms
Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
37th Conference on Neural Information Processing Systems (NeurIPS 2023).
Accepted for oral presentation.

Agnostic Proper Learning of Monotone Functions: Beyond the Black-box Correction Barrier
Jane Lange and Arsen Vasilyan
64th IEEE Symposium on Foundations of Computer Science (FOCS 2023).
Invited to special issue.

Testing Distributional Assumptions of Learning Algorithms
Ronitt Rubinfeld, Arsen Vasilyan
55th ACM Symposium on Theory of Computing (STOC 2023)

Properly Learning Monotone Functions via Local Reconstruction
Jane Lange, Ronitt Rubinfeld, Arsen Vasilyan
63rd IEEE Symposium on Foundations of Computer Science (FOCS 2022)

Monotone Probability Distributions over the Boolean Cube Can Be Learned with Sublinear Samples
Ronitt Rubinfeld, Arsen Vasilyan
11th Innovations in Theoretical Computer Science Conference (ITCS 2020)

Approximating the Noise Sensitivity of a Monotone Boolean Function
Ronitt Rubinfeld, Arsen Vasilyan
Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques
(APPROX/RANDOM 2019).

Preprints:

Testable Learning with Distribution Shift
Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
Preprint arXiv:2311.15142(2023).

Local Lipschitz Filters for Bounded-Range Functions
Jane Lange, Ephraim Linder, Sofya Raskhodnikova, Arsen Vasilyan
Preprint arXiv:2308.14716 (2023).