Sushrut Karmalkar

Publications

  1. Approximation Schemes for ReLU Regression
    Ilias Diakonikolas, Surbhi Goel, Sushrut Karmalkar , Adam Klivans and Mahdi Soltanolkotabi
    Conference on Learning Theory (COLT) 2020
    [arxiv]
  2. Robustly Learning any Clusterable Mixture of Gaussians
    Ilias Diakonikolas, Samuel B. Hopkins, Daniel Kane, Sushrut Karmalkar
    IEEE Symposium on Foundations of Computer Science (FOCS) 2020
    [arxiv]
  3. On the Power of Compressed Sensing with Generative Models
    Akshay Kamath, Sushrut Karmalkar and Eric Price
    International Conference on Machine Learning (ICML) 2020
    [arxiv]
  4. Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent
    Surbhi Goel, Aravind Gollakota, Zhihan Jin, Sushrut Karmalkar and Adam Klivans
    International Conference on Machine Learning (ICML) 2020
    [arxiv]
  5. Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals
    Surbhi Goel, Sushrut Karmalkar and Adam Klivans
    Neural Information Processing Systems (NeurIPS) 2019 (Spotlight)
    [arxiv]
  6. List decodeable linear regression
    Sushrut Karmalkar , Adam Klivans and Pravesh Kothari
    Neural Information Processing Systems (NeurIPS) 2019 (Spotlight)
    [arxiv]
  7. Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering.
    Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar Eric Price and Alistair Stewart
    Neural Information Processing Systems (NeurIPS) 2019
    [arxiv]
  8. Compressed Sensing with Adversarial Sparse Noise via L1 Regression.
    Sushrut Karmalkar and Eric Price
    Symposium on Simplicity in Algorithms (SOSA) 2019
    [arxiv]
  9. Fourier Entropy-Influence Conjecture for Random Linear Threshold Functions
    Sourav Chakraborty, Sushrut Karmalkar , Srijita Kundu, Satyanarayana V. Lokam and Nitin Saurabh
    Latin American Symposium on Theoretical Informatics (LATIN) 2018
    [arxiv]
  10. Robust Polynomial Regression up to the Information Theoretic Limit
    Daniel Kane, Sushrut Karmalkar and Eric Price
    IEEE Symposium on Foundations of Computer Science (FOCS) 2017
    [arxiv]

Awards

  1. University Graduate Continuing Fellowship (2020-2021) UT Austin
  2. Graduate School Summer Fellowship (2018) UT Austin
  3. CMI Fellowship for Masters students
  4. CMI Fellowship for Undergraduate students