Publications
> Preprints
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Robust Streaming Against Low-Memory Adversaries
Omri Ben-Eliezer, Krzysztof Onak, Sandeep Silwal
Preprint [pdf] -
Even Faster Kernel Matrix Linear Algebra via Density Estimation
Rikhav Shah, Sandeep Silwal, Haike Xu
Preprint [pdf] -
Hypothesis Selection: A High Probability Conundrum
Anders Aamand, Maryam Aliakbarpour, Justin Y. Chen, Sandeep Silwal
Preprint [pdf] -
A Bi-metric Framework for Fast Similarity Search
Haike Xu*, Sandeep Silwal, Piotr Indyk
Best Paper Award at The 1st Workshop on Vector Databases, ICML 2025
Preprint [pdf] -
Dimension Reduction for Clustering: The Curious Case of Discrete Centers
Shaofeng Jiang, Robert Krauthgamer, Shay Sapir, Sandeep Silwal, Di Yue
Preprint [pdf]
> 2026
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On the Structure of Replicable Hypothesis Testers
Anders Aamand, Maryam Aliakbarpour, Justin Y. Chen, Shyam Narayanan, Sandeep Silwal
SODA 2026 [pdf]
> 2025
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Efficient Training-Free Online Routing for High-Volume Multi-LLM Serving
Fangzhou Wu, Sandeep Silwal
NeurIPS 2025 [pdf] -
Differentially Private Gomory-Hu Trees
Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard, Slobodan Mitrović, Yuriy Nevmyvaka, Sandeep Silwal, Yinzhan Xu
NeurIPS 2025 [pdf] -
Breaking the $n^{1.5}$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition
Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard, Slobodan Mitrović, Yuriy Nevmyvaka, Sandeep Silwal, Yinzhan Xu
ICML 2025 [pdf] -
Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures
Jie Gao, Rajesh Jayaram, Benedikt Kolbe, Shay Sapir, Chris Schwiegelshohn, Sandeep Silwal, Erik Waingarten
ICML 2025 [pdf] -
Improved Approximations for Hard Graph Problems using Predictions
Anders Aamand, Justin Y. Chen, Siddharth Gollapudi, Sandeep Silwal, Hao Wu
ICML 2025 [pdf] -
Learning-Augmented Frequent Directions
Anders Aamand, Justin Y. Chen, Siddharth Gollapudi, Sandeep Silwal, Hao WU
Spotlight Presentation at ICLR 2025 [pdf] -
Beyond Worst-Case Dimensionality Reduction for Sparse Vectors
Sandeep Silwal, David Woodruff, Qiuyi Zhang
ICLR 2025 [pdf] -
Optimal and learned algorithms for the online list update problem with Zipfian accesses
Piotr Indyk, Isabelle Quaye, Ronitt Rubinfeld, Sandeep Silwal
ALT 2025 [pdf]
> 2024
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Statistical-Computational Tradeoffs for Density Estimation
Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Haike Xu
NeurIPS 2024 [pdf] -
Optimal Algorithms for Augmented Testing of Discrete Distributions
Maryam Aliakbarpour, Piotr Indyk, Ronitt Rubinfeld, Sandeep Silwal
NeurIPS 2024 [pdf] -
Efficiently Computing Similarities to Private Datasets
Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski
ICLR 2024 [pdf]
> 2023
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Improved Frequency Estimation Algorithms with and without Predictions
Anders Aamand, Justin Y. Chen, Huy Nguyen, Sandeep Silwal, Ali Vakilian
Spotlight Presentation at NeurIPS 2023 [pdf] -
A Near-Linear Time Algorithm for the Chamfer Distance
Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten
NeurIPS 2023 [pdf] -
Constant Approximation for Individual Preference Stable Clustering
Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang
Spotlight Presentation at NeurIPS 2023 [pdf] -
Data Structures for Density Estimation
Anders Aamand, Alexandr Andoni, Justin Y Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal
ICML 2023 [pdf] -
KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals
Sandeep Silwal*, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran, Seyed Mehran Kazemi
ICLR 2023 [pdf] -
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation
Ainesh Bakshi, Praneeth Kacham, Piotr Indyk, Sandeep Silwal, Samson Zhou
Spotlight Presentation at ICLR 2023 [pdf] -
Robust Algorithms on Adaptive Inputs from Bounded Adversaries
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou
ICLR 2023 [pdf] -
Learned Interpolation for Better Streaming Quantile Approximation with Worst Case Guarantees
Nicholas Schiefer*, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Tal Wagner
ACDA 2023 [pdf] -
Improved Space Bounds for Learning with Experts
Anders Aamand, Justin Y. Chen, Huy Lê Nguyễn, Sandeep Silwal
ACDA 2023 (Poster) [pdf] -
Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou
SODA 2023 [pdf]
> 2022
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Faster Linear Algebra for Distance Matrices
Piotr Indyk, Sandeep Silwal
Oral Presentation at NeurIPS 2022 [pdf] -
Learning-Augmented Algorithms for Online Linear and Semidefinite Programming
Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou
NeurIPS 2022 [pdf] -
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] -
Faster Fundamental Graph Algorithms via Learned Predictions
Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang
ICML 2022 [pdf] -
Hardness and Algorithms for Robust and Sparse Optimization
Eric Price, Sandeep Silwal, Samson Zhou
ICML 2022 [pdf] -
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] -
Learning-Augmented $k$-means Clustering
Jon Ergun, Zhili Feng, Sandeep Silwal, David Woodruff, Samson Zhou
Spotlight Presentation at ICLR 2022 [pdf] -
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] -
Motif Cut Sparsifiers
Michael Kapralov, Mikhail Makarov, Sandeep Silwal, Christian Sohler, Jakab Tardos
FOCS 2022 [pdf]
> 2021
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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] -
Dimensionality Reduction for Wasserstein Barycenter
Zachary Izzo, Sandeep Silwal, Samson Zhou
NeurIPS 2021 [pdf] -
Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering
Shyam Narayanan*, Sandeep Silwal*, Piotr Indyk, Or Zamir
ICML 2021 [pdf] -
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] -
Smoothed Analysis of the Condition Number Under Low-Rank Perturbations
Rikhav Shah, Sandeep Silwal
RANDOM 2021 [pdf]