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Research

My interests broadly lie in machine learning and algorithm design, and I have done work related to optimal transport algorithms and statistical learning theory.

Preprints

Tradeoffs between Mistakes and ERM Oracle Calls in Online and Transductive Online Learning. Idan Attias, Steve Hanneke, Arvind Ramaswami

Publications

2025

Attias, I., Hanneke, S., and Ramaswami, A. (2025). Sample Compression Scheme Reductions. In Proceedings of the 36th International Conference on Algorithmic Learning Theory (ALT). arxiv

2023

Chen, J., Chen, L., Liu, Y. P., Peng, R., & Ramaswami, A. (2023). Exponential Convergence of Sinkhorn Under Regularization Scheduling. In SIAM Conference on Applied and Computational Discrete Algorithms (ACDA23) (pp. 180-188). Society for Industrial and Applied Mathematics. arxiv, Proceedings, SIAM ACDA 2023

Other writeups (Class projects)

SDPs for MaxCut Approximations (2021, Final project in MATH 7014 - Advanced Graph Theory). (Survey, Presentation)

SQ Learning for Tensor PCA (2021, Research report in CS7545 - Machine Learning Theory) (Survey)