Sandeep Silwal

88 papers A* 31A 3B 1Journal 50Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	A	`conf`	Dimension Reduction for Clustering: The Curious Case of Discrete Centers. ITCS Shaofeng H.-C. Jiang, Robert Krauthgamer, Shay Sapir, Sandeep Silwal, Di Yue
2026	A*	`conf`	On the Structure of Replicable Hypothesis Testers. SODA Anders Aamand, Maryam Aliakbarpour, Justin Y. Chen, Shyam Narayanan, Sandeep Silwal
2026	J	`jnl`	Randomization Boosts KV Caching, Learning Balances Query Load: A Joint Perspective. CoRR Fangzhou Wu, Sandeep Silwal, Qiuyi Zhang
2026	A	`conf`	Robust Streaming Against Low-Memory Adversaries. ITCS Omri Ben-Eliezer, Krzysztof Onak, Sandeep Silwal
2026	J	`jnl`	Skirting Additive Error Barriers for Private Turnstile Streams. CoRR Anders Aamand, Justin Y. Chen, Sandeep Silwal
2025	A*	`conf`	Beyond Worst-Case Dimensionality Reduction for Sparse Vectors. ICLR Sandeep Silwal, David P. Woodruff, Qiuyi Zhang
2025	J	`jnl`	Beyond Worst-Case Dimensionality Reduction for Sparse Vectors. CoRR Sandeep Silwal, David P. Woodruff, Qiuyi Zhang
2025	J	`jnl`	Breaking the n CoRR Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard, Slobodan Mitrovic, Yuriy Nevmyvaka, Sandeep Silwal, Yinzhan Xu
2025	A*	`conf`	Breaking the n1.5 Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition. ICML Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard, Slobodan Mitrovic, Yuriy Nevmyvaka, Sandeep Silwal, Yinzhan Xu
2025	J	`jnl`	Cluster Tree for Nearest Neighbor Search. Trans. Mach. Learn. Res. Dan Kushnir, Sandeep Silwal
2025	J	`jnl`	Dimension Reduction for Clustering: The Curious Case of Discrete Centers. CoRR Shaofeng H.-C. Jiang, Robert Krauthgamer, Shay Sapir, Sandeep Silwal, Di Yue
2025	J	`jnl`	Efficient Training-Free Online Routing for High-Volume Multi-LLM Serving. CoRR Fangzhou Wu, Sandeep Silwal
2025	J	`jnl`	Even Faster Kernel Matrix Linear Algebra via Density Estimation. CoRR Rikhav Shah, Sandeep Silwal, Haike Xu
2025	J	`jnl`	Hypothesis Selection: A High Probability Conundrum. CoRR Anders Aamand, Maryam Aliakbarpour, Justin Y. Chen, Sandeep Silwal
2025	A*	`conf`	Improved Approximations for Hard Graph Problems using Predictions. ICML Anders Aamand, Justin Y. Chen, Siddharth Gollapudi, Sandeep Silwal, Hao Wu
2025	J	`jnl`	Improved Approximations for Hard Graph Problems using Predictions. CoRR Anders Aamand, Justin Y. Chen, Siddharth Gollapudi, Sandeep Silwal, Hao Wu
2025	A*	`conf`	Learning-Augmented Frequent Directions. ICLR Anders Aamand, Justin Y. Chen, Siddharth Gollapudi, Sandeep Silwal, Hao Wu
2025	J	`jnl`	Learning-Augmented Frequent Directions. CoRR Anders Aamand, Justin Y. Chen, Siddharth Gollapudi, Sandeep Silwal, Hao Wu
2025	J	`jnl`	On the Structure of Replicable Hypothesis Testers. CoRR Anders Aamand, Maryam Aliakbarpour, Justin Y. Chen, Shyam Narayanan, Sandeep Silwal
2025	B	`conf`	Optimal and learned algorithms for the online list update problem with Zipfian accesses. ALT Piotr Indyk, Isabelle Quaye, Ronitt Rubinfeld, Sandeep Silwal
2025	A*	`conf`	Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures. ICML Jie Gao, Rajesh Jayaram, Benedikt Kolbe, Shay Sapir, Chris Schwiegelshohn, Sandeep Silwal, Erik Waingarten
2025	J	`jnl`	Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures. CoRR Jie Gao, Rajesh Jayaram, Benedikt Kolbe, Shay Sapir, Chris Schwiegelshohn, Sandeep Silwal, Erik Waingarten
2025	J	`jnl`	Robust Streaming Against Low-Memory Adversaries. CoRR Omri Ben-Eliezer, Krzysztof Onak, Sandeep Silwal
2024	J	`jnl`	A Bi-metric Framework for Fast Similarity Search. CoRR Haike Xu, Sandeep Silwal, Piotr Indyk
2024	J	`jnl`	Differentially Private Gomory-Hu Trees. CoRR Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard, Slobodan Mitrovic, Yuriy Nevmyvaka, Sandeep Silwal, Yinzhan Xu
2024	A*	`conf`	Efficiently Computing Similarities to Private Datasets. ICLR Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski
2024	J	`jnl`	Efficiently Computing Similarities to Private Datasets. CoRR Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski
2024	A*	`conf`	Optimal Algorithms for Augmented Testing of Discrete Distributions. NeurIPS Maryam Aliakbarpour, Piotr Indyk, Ronitt Rubinfeld, Sandeep Silwal
2024	J	`jnl`	Optimal Algorithms for Augmented Testing of Discrete Distributions. CoRR Maryam Aliakbarpour, Piotr Indyk, Ronitt Rubinfeld, Sandeep Silwal
2024	A*	`conf`	Statistical-Computational Trade-offs for Density Estimation. NeurIPS Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Haike Xu
2024	J	`jnl`	Statistical-Computational Trade-offs for Density Estimation. CoRR Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Haike Xu
2023	J	`jnl`	A Near-Linear Time Algorithm for the Chamfer Distance. CoRR Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten
2023	A*	`conf`	Constant Approximation for Individual Preference Stable Clustering. NeurIPS Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang
2023	J	`jnl`	Constant Approximation for Individual Preference Stable Clustering. CoRR Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang
2023	A*	`conf`	Data Structures for Density Estimation. ICML Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal
2023	J	`jnl`	Data Structures for Density Estimation. CoRR Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal
2023	A*	`conf`	Improved Frequency Estimation Algorithms with and without Predictions. NeurIPS Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal, Ali Vakilian
2023	J	`jnl`	Improved Frequency Estimation Algorithms with and without Predictions. CoRR Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal, Ali Vakilian
2023	J	`jnl`	Improved Space Bounds for Learning with Experts. CoRR Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal
2023	A*	`conf`	KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals. ICLR Sandeep Silwal, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran, Seyed Mehran Kazemi
2023	—	`conf`	KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals. SustaiNLP Sandeep Silwal, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran, Seyed Mehran Kazemi
2023	—	`conf`	Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees. ACDA Nicholas Schiefer, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Tal Wagner
2023	J	`jnl`	Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees. CoRR Nicholas Schiefer, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Tal Wagner
2023	A*	`conf`	Near-Linear Time Algorithm for the Chamfer Distance. NeurIPS Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten
2023	A*	`conf`	Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. SODA Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou
2023	A*	`conf`	Robust Algorithms on Adaptive Inputs from Bounded Adversaries. ICLR Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou
2023	J	`jnl`	Robust Algorithms on Adaptive Inputs from Bounded Adversaries. CoRR Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou
2023	A*	`conf`	Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation. ICLR Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
2022	J	`jnl`	A concentration inequality for the facility location problem. Oper. Res. Lett. Sandeep Silwal
2022	A*	`conf`	Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks. NeurIPS Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner
2022	J	`jnl`	Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks. CoRR Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner
2022	A*	`conf`	Faster Fundamental Graph Algorithms via Learned Predictions. ICML Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang
2022	J	`jnl`	Faster Fundamental Graph Algorithms via Learned Predictions. CoRR Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang
2022	A*	`conf`	Faster Linear Algebra for Distance Matrices. NeurIPS Piotr Indyk, Sandeep Silwal
2022	J	`jnl`	Faster Linear Algebra for Distance Matrices. CoRR Piotr Indyk, Sandeep Silwal
2022	A*	`conf`	Hardness and Algorithms for Robust and Sparse Optimization. ICML Eric Price, Sandeep Silwal, Samson Zhou
2022	J	`jnl`	Hardness and Algorithms for Robust and Sparse Optimization. CoRR Eric Price, Sandeep Silwal, Samson Zhou
2022	A*	`conf`	Learning-Augmented $k$-means Clustering. ICLR Jon C. Ergun, Zhili Feng, Sandeep Silwal, David P. Woodruff, Samson Zhou
2022	A*	`conf`	Learning-Augmented Algorithms for Online Linear and Semidefinite Programming. NeurIPS Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou
2022	J	`jnl`	Learning-Augmented Algorithms for Online Linear and Semidefinite Programming. CoRR Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou
2022	A*	`conf`	Motif Cut Sparsifiers. FOCS Michael Kapralov, Mikhail Makarov, Sandeep Silwal, Christian Sohler, Jakab Tardos
2022	J	`jnl`	Motif Cut Sparsifiers. CoRR Michael Kapralov, Mikhail Makarov, Sandeep Silwal, Christian Sohler, Jakab Tardos
2022	J	`jnl`	Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. CoRR Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou
2022	J	`jnl`	Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation. CoRR Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
2022	A*	`conf`	The White-Box Adversarial Data Stream Model. PODS Miklós Ajtai, Vladimir Braverman, T. S. Jayram, Sandeep Silwal, Alec Sun, David P. Woodruff, Samson Zhou
2022	J	`jnl`	The White-Box Adversarial Data Stream Model. CoRR Miklós Ajtai, Vladimir Braverman, T. S. Jayram, Sandeep Silwal, Alec Sun, David P. Woodruff, Samson Zhou
2022	A*	`conf`	Triangle and Four Cycle Counting with Predictions in Graph Streams. ICLR Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang
2022	J	`jnl`	Triangle and Four Cycle Counting with Predictions in Graph Streams. CoRR Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang
2021	A*	`conf`	Adversarial Robustness of Streaming Algorithms through Importance Sampling. NeurIPS Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou
2021	J	`jnl`	Adversarial Robustness of Streaming Algorithms through Importance Sampling. CoRR Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou
2021	A*	`conf`	Dimensionality Reduction for Wasserstein Barycenter. NeurIPS Zachary Izzo, Sandeep Silwal, Samson Zhou
2021	J	`jnl`	Dimensionality Reduction for Wasserstein Barycenter. CoRR Zachary Izzo, Sandeep Silwal, Samson Zhou
2021	J	`jnl`	Learning-Augmented k-means Clustering. CoRR Jon Ergun, Zhili Feng, Sandeep Silwal, David P. Woodruff, Samson Zhou
2021	A*	`conf`	Learning-based Support Estimation in Sublinear Time. ICLR Talya Eden, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner
2021	J	`jnl`	Learning-based Support Estimation in Sublinear Time. CoRR Talya Eden, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner
2021	A*	`conf`	Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering. ICML Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir
2021	J	`jnl`	Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering. CoRR Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir
2021	—	`conf`	Smoothed Analysis of the Condition Number Under Low-Rank Perturbations. APPROX-RANDOM Rikhav Shah, Sandeep Silwal
2020	J	`jnl`	A Concentration Inequality for the Facility Location Problem. CoRR Sandeep Silwal
2020	A*	`conf`	Property Testing of LP-Type Problems. ICALP Rogers Epstein, Sandeep Silwal
2020	J	`jnl`	Smoothed analysis of the condition number under low-rank perturbations. CoRR Rikhav Shah, Sandeep Silwal
2020	A	`conf`	Testing Properties of Multiple Distributions with Few Samples. ITCS Maryam Aliakbarpour, Sandeep Silwal
2019	J	`jnl`	Directed random geometric graphs. J. Complex Networks Jesse Michel, Sushruth Reddy, Rikhav Shah, Sandeep Silwal, Ramis Movassagh
2019	J	`jnl`	Property Testing of LP-Type Problems. CoRR Rogers Epstein, Sandeep Silwal
2019	J	`jnl`	Testing Properties of Multiple Distributions with Few Samples. CoRR Maryam Aliakbarpour, Sandeep Silwal
2019	J	`jnl`	Using Dimensionality Reduction to Optimize t-SNE. CoRR Rikhav Shah, Sandeep Silwal
2018	J	`jnl`	Directed Random Geometric Graphs. CoRR Jesse Michel, Sushruth Reddy, Rikhav Shah, Sandeep Silwal, Ramis Movassagh
2018	J	`jnl`	Spectral methods for testing cluster structure of graphs. CoRR Sandeep Silwal, Jonathan Tidor