Faster Fundamental Graph Algorithms via Learned Predictions
Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang
ICML 2022 [pdf] [story]
Triangle and Four Cycle Counting with Predictions in Graph Stream
Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David Woodruff, Michael Zhang
ICLR 2022 [pdf] [story] [slides] [code]
Learning-Augmented $k$-means Clustering
Jon Ergun, Zhili Feng, Sandeep Silwal, David Woodruff, Samson Zhou
Spotlight Presentation at ICLR 2022 [pdf] [story] [slides]
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] [story] [video] [poster]
Faster Linear Algebra for Distance Matrices
Piotr Indyk, Sandeep Silwal
Oral at NeurIPS 2022 [pdf] [story] [slides]
The White-Box Adversarial Data Stream Model
Miklos Ajtai, Vladimir Braverman, T.S. Jayram, Sandeep Silwal, Alec Sun, David P. Woodruff, Samson Zhou
PODS 2022 [pdf] [story] [slides]
Adversarial Robustness of Streaming Algorithms through Importance Sampling
Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou
Silver Best Paper Award at Adversarial ML Workshop at ICML 2021; Final version at NeurIPS 2021
[pdf] [story] [video] [slides]
Property Testing of LP-Type Problems
Rogers Epstein, Sandeep Silwal
ICALP 2020 [pdf] [story] [video]
Testing Properties of Multiple Distributions with Few Samples
Maryam Aliakbarpour, Sandeep Silwal
ITCS 2020 [pdf] [story] [video]
Dimensionality Reduction for Wasserstein Barycenter
Zachary Izzo, Sandeep Silwal, Samson Zhou
NeurIPS 2021 [pdf] [story] [video]
Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering
Shyam Narayanan*, Sandeep Silwal*, Piotr Indyk, Or Zamir
ICML 2021 [pdf] [story] [video]
Using Dimensionality Reduction to Optimize t-SNE
Rikhav Shah, Sandeep Silwal
OPTML Workshop at NeurIPS 2019 [pdf] [story] [poster]
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks
Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Nicholas Schiefer, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner
NeurIPS 2022 [pdf][story] [slides]
Hardness and Algorithms for Robust and Sparse Optimization
Eric Price, Sandeep Silwal, Samson Zhou
ICML 2022 [pdf] [story] [slides]
Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou
SODA 2023 [pdf coming soon!]
Motif Cut Sparsifiers
Michael Kapralov, Mikhail Makarov, Sandeep Silwal, Christian Sohler, Jakab Tardos
FOCS 2022 [pdf] [story coming soon!]
Smoothed Analysis of the Condition Number Under Low-Rank Perturbations
Rikhav Shah, Sandeep Silwal
RANDOM 2021 [pdf] [story] [video]
A Concentration Inequality for the Facility Location Problem
Sandeep Silwal
Operations Research Letters, Volume 50 [pdf] [story]
A note on the universality of ESDs of inhomogeneous random matrices
Vishesh Jain, Sandeep Silwal
Latin American Journal of Probability and Mathematical Statistics [pdf]
Directed Random Geometric Graphs
Jesse Michel, Ramis Movassagh, Sushruth Reddy, Rikhav Shah, Sandeep Silwal
Journal of Complex Networks [pdf] [story]