Prayaag Venkat     About     Archive

About

I am a third-year graduate student in the theory of computation group at Harvard University, advised by Boaz Barak.

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.

Papers

  • Preetum Nakkiran, Prayaag Venkat, Sham Kakade, Tengyu Ma. Optimal Regularization Can Mitigate Double Descent The Ninth International Conference on Learning Representations (ICLR 2021). [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]

Contact

CV | GitHub | Email


Last updated: 03/19/2021