Sandeep Silwal

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 60

Top Topics

Facility Location

Cluster Structure

Kernel Density Estimation

Top Venues

Publications

Haike Xu, Sandeep Silwal, Piotr Indyk
A Bi-metric Framework for Fast Similarity Search. CoRR (2024)
Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski
Efficiently Computing Similarities to Private Datasets. ICLR (2024)
Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski
Efficiently Computing Similarities to Private Datasets. CoRR (2024)
Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten
Near-Linear Time Algorithm for the Chamfer Distance. NeurIPS (2023)
Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang
Constant Approximation for Individual Preference Stable Clustering. CoRR (2023)
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou
Robust Algorithms on Adaptive Inputs from Bounded Adversaries. CoRR (2023)
Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten
A Near-Linear Time Algorithm for the Chamfer Distance. CoRR (2023)
Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal, Ali Vakilian
Improved Frequency Estimation Algorithms with and without Predictions. CoRR (2023)
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou
Robust Algorithms on Adaptive Inputs from Bounded Adversaries. ICLR (2023)
Nicholas Schiefer, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Tal Wagner
Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees. CoRR (2023)
Sandeep Silwal, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran, Seyed Mehran Kazemi
KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals. SustaiNLP (2023)
Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal
Improved Space Bounds for Learning with Experts. CoRR (2023)
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou
Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. SODA (2023)
Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal
Data Structures for Density Estimation. CoRR (2023)
Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal, Ali Vakilian
Improved Frequency Estimation Algorithms with and without Predictions. NeurIPS (2023)
Nicholas Schiefer, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Tal Wagner
Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees. ACDA (2023)
Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang
Constant Approximation for Individual Preference Stable Clustering. NeurIPS (2023)
Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal
Data Structures for Density Estimation. ICML (2023)
Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation. ICLR (2023)
Sandeep Silwal, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran, Seyed Mehran Kazemi
KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals. ICLR (2023)
Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou
Learning-Augmented Algorithms for Online Linear and Semidefinite Programming. NeurIPS (2022)
Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang
Faster Fundamental Graph Algorithms via Learned Predictions. CoRR (2022)
Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks. CoRR (2022)
Michael Kapralov, Mikhail Makarov, Sandeep Silwal, Christian Sohler, Jakab Tardos
Motif Cut Sparsifiers. CoRR (2022)
Miklós Ajtai, Vladimir Braverman, T. S. Jayram, Sandeep Silwal, Alec Sun, David P. Woodruff, Samson Zhou
The White-Box Adversarial Data Stream Model. CoRR (2022)
Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang
Triangle and Four Cycle Counting with Predictions in Graph Streams. CoRR (2022)
Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang
Triangle and Four Cycle Counting with Predictions in Graph Streams. ICLR (2022)
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou
Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. CoRR (2022)
Michael Kapralov, Mikhail Makarov, Sandeep Silwal, Christian Sohler, Jakab Tardos
Motif Cut Sparsifiers. FOCS (2022)
Jon C. Ergun, Zhili Feng, Sandeep Silwal, David P. Woodruff, Samson Zhou
Learning-Augmented $k$-means Clustering. ICLR (2022)
Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou
Learning-Augmented Algorithms for Online Linear and Semidefinite Programming. CoRR (2022)
Piotr Indyk, Sandeep Silwal
Faster Linear Algebra for Distance Matrices. NeurIPS (2022)
Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang
Faster Fundamental Graph Algorithms via Learned Predictions. ICML (2022)
Eric Price, Sandeep Silwal, Samson Zhou
Hardness and Algorithms for Robust and Sparse Optimization. CoRR (2022)
Miklós Ajtai, Vladimir Braverman, T. S. Jayram, Sandeep Silwal, Alec Sun, David P. Woodruff, Samson Zhou
The White-Box Adversarial Data Stream Model. PODS (2022)
Piotr Indyk, Sandeep Silwal
Faster Linear Algebra for Distance Matrices. CoRR (2022)
Sandeep Silwal
A concentration inequality for the facility location problem. Oper. Res. Lett. 50 (2) (2022)
Eric Price, Sandeep Silwal, Samson Zhou
Hardness and Algorithms for Robust and Sparse Optimization. ICML (2022)
Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks. NeurIPS (2022)
Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation. CoRR (2022)
Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou
Adversarial Robustness of Streaming Algorithms through Importance Sampling. NeurIPS (2021)
Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou
Adversarial Robustness of Streaming Algorithms through Importance Sampling. CoRR (2021)
Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir
Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering. ICML (2021)
Zachary Izzo, Sandeep Silwal, Samson Zhou
Dimensionality Reduction for Wasserstein Barycenter. CoRR (2021)
Jon Ergun, Zhili Feng, Sandeep Silwal, David P. Woodruff, Samson Zhou
Learning-Augmented k-means Clustering. CoRR (2021)
Zachary Izzo, Sandeep Silwal, Samson Zhou
Dimensionality Reduction for Wasserstein Barycenter. NeurIPS (2021)
Rikhav Shah, Sandeep Silwal
Smoothed Analysis of the Condition Number Under Low-Rank Perturbations. APPROX-RANDOM (2021)
Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir
Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering. CoRR (2021)
Talya Eden, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner
Learning-based Support Estimation in Sublinear Time. CoRR (2021)
Talya Eden, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner
Learning-based Support Estimation in Sublinear Time. ICLR (2021)
Rikhav Shah, Sandeep Silwal
Smoothed analysis of the condition number under low-rank perturbations. CoRR (2020)
Maryam Aliakbarpour, Sandeep Silwal
Testing Properties of Multiple Distributions with Few Samples. ITCS (2020)
Rogers Epstein, Sandeep Silwal
Property Testing of LP-Type Problems. ICALP (2020)
Sandeep Silwal
A Concentration Inequality for the Facility Location Problem. CoRR (2020)
Rikhav Shah, Sandeep Silwal
Using Dimensionality Reduction to Optimize t-SNE. CoRR (2019)
Rogers Epstein, Sandeep Silwal
Property Testing of LP-Type Problems. CoRR (2019)
Jesse Michel, Sushruth Reddy, Rikhav Shah, Sandeep Silwal, Ramis Movassagh
Directed random geometric graphs. J. Complex Networks 7 (5) (2019)
Maryam Aliakbarpour, Sandeep Silwal
Testing Properties of Multiple Distributions with Few Samples. CoRR (2019)
Sandeep Silwal, Jonathan Tidor
Spectral methods for testing cluster structure of graphs. CoRR (2018)
Jesse Michel, Sushruth Reddy, Rikhav Shah, Sandeep Silwal, Ramis Movassagh
Directed Random Geometric Graphs. CoRR (2018)