Sandeep Silwal

I am a third year graduate student at MIT where I am lucky to be advised by Piotr Indyk . My research interests are broadly in theoretical computer science. Recently, I've been working in the Intersection of machine learning and classical algorithms, such as designing provable algorithms in various ML settings as well as using ML to inspire algorithm design. Previously, I have dabbled in sublinear algorithms, property testing, and various problems in probability.

I also help coordinate Algorithms Office Hours at MIT whose goal is to improve communication between theory and applications of algorithms.

You can contact me at {my last name}@mit.edu.

Publications

  1. Adversarial Robustness of Streaming Algorithms through Importance Sampling. Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou. NeurIPS 2021. Silver Best Paper Award at Adversarial ML Workshop at ICML 2021. [pdf]

  2. Dimensionality Reduction for Wasserstein Barycenter Zachary Izzo, Sandeep Silwal, Samson Zhou. NeurIPS 2021. [link coming soon!]

  3. Smoothed Analysis of the Condition Number Under Low-Rank Perturbations. Rikhav Shah, Sandeep Silwal. RANDOM 2021. [pdf]

  4. Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering. Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir. ICML 2021. [pdf]

  5. Learning-based Support Estimation in Sublinear Time. Talya Eden, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner. Spotlight Presentation at ICLR 2021. [pdf]

  6. A note on the universality of ESDs of inhomogeneous random matrices . Vishesh Jain, Sandeep Silwal. Latin American Journal of Probability and Mathematical Statistics. [pdf]

  7. Property Testing of LP-Type Problems. Rogers Epstein, Sandeep Silwal. ICALP 2020. [pdf]

  8. Testing Properties of Multiple Distributions with Few Samples. Maryam Aliakbarpour, Sandeep Silwal. ITCS 2020. [pdf]

  9. Using Dimensionality Reduction to Optimize t-SNE. Rikhav Shah, Sandeep Silwal. OPTML Workshop at NeurIPS 2019. [pdf]

  10. Directed Random Geometric Graphs. Jesse Michel, Ramis Movassagh, Sushruth Reddy, Rikhav Shah, Sandeep Silwal. Journal of Complex Networks. [pdf]

Manuscripts