I am a third-year graduate student in the theory of computation group at Harvard University, advised by Boaz Barak. I am currently visiting Prasad Raghavendra at UC Berkeley and participating in the HD20 Simons Institute program.
I am interested in the connections between: the Sum-of-Squares SDP hierarchy, statistical physics, average-case complexity theory, and information-computation gaps in high-dimensional statistics problems.
My graduate studies are supported by an NSF Graduate Fellowship.
Preetum Nakkiran, Prayaag Venkat, Sham Kakade, Tengyu Ma. Optimal Regularization Can Mitigate Double Descent In submission. [arXiv:2003.01897]
Zhixian Lei, Kyle Luh, Prayaag Venkat, Fred Zhang.
A Fast Spectral Algorithm for Mean Estimation with Sub-Gaussian Rates
The 33rd Annual Conference on Learning Theory (COLT 2020) [arXiv:1908.04468]
Samir Khuller, Jingling Li, Pascal Sturmfels, Kevin Sun, and Prayaag Venkat.
Select and Permute: An Improved Online Framework for Scheduling to Minimize Weighted Completion Time
The 13th Latin American Theoretical Informatics Symposium (LATIN 2018) [arXiv:1704.06677]
Prayaag Venkat and David Mount.
A Succinct, Dynamic Data Structure for Proximity Queries on Point Sets
The 26th Canadian Conference on Computational Geometry (CCCG 2014) [link]
Last updated: 08/27/2020