Publications

Deeksha Adil, Jarosław Błasiok, Hongjie Chen, Deepak Narayan Sridharan (2026). On efficient robust regression with subquadratic samples. Proceedings of Thirty Ninth Conference on Learning Theory (COLT 2026).
arxiv
Jarosław Błasiok, Paul Lou, Alon Rosen, Madhu Sudan (2026). Expanders Meet Reed-Muller: Easy Instances of Noisy k-XOR. FOCS 2026.
arxiv
Deeksha Adil, Jarosław Błasiok (2026). Efficient and Provable Algorithms for Covariate Shift. Proceedings of The 37th International Conference on Algorithmic Learning Theory.
arxiv
Afonso S. Bandeira, Jarosław Błasiok, Daniil Dmitriev, Ulysse Faure, Anastasia Kireeva, Dmitriy Kunisky (2025). The Lovász number of random circulant graphs. 2025 International Conference on Sampling Theory and Applications (SampTA).
arxiv DOI
Jarosław Błasiok, Linus Meierhöfer (2025). Hardness of clique approximation for monotone circuits. Proceedings of the 40th Computational Complexity Conference.
arxiv DOI
Jarosław Błasiok, Rares Buhai, Pravesh Kothari, David Steurer (2024). Semirandom Planted Clique and the Restricted Isometry Property. STOC 2024.
arxiv
Jarosław Błasiok, Preetum Nakkiran (2024). Smooth ECE: Principled Reliability Diagrams via Kernel Smoothing. ICLR 2024.
arxiv
Jarosław Błasiok, Parikshit Gopalan, Lunjia Hu, Adam Tauman Kalai, Preetum Nakkiran (2024). Loss minimization yields multicalibration for large neural networks. ITCS 2024.
arxiv
Jarosław Błasiok, Parikshit Gopalan, Lunjia Hu, Preetum Nakkiran (2023). When Does Optimizing a Proper Loss Yield Calibration?. NeurIPS 2023.
arxiv
Josh Alman, Jarosław Błasiok (2023). Matrix Multiplication and Number On the Forehead Communication. CCC 2023.
arxiv