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20192026
most citedAdversarial Robustness of Streaming Algorithms through Importance Sampling

15 citations · 51 across the 40 of their papers we have counts for

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10 papers · 1 filter

cs.DS2025

Robust Streaming Against Low-Memory Adversaries

Omri Ben-Eliezer, Krzysztof Onak, Sandeep Silwal

Robust streaming, the study of streaming algorithms that provably work when the stream is generated by an adaptive adversary, has seen tremendous progress in recent years. However,…

cs.DS2025

Dimension Reduction for Clustering: The Curious Case of Discrete Centers

Shaofeng H. -C. Jiang, Robert Krauthgamer, Shay Sapir +2

The Johnson-Lindenstrauss transform is a fundamental method for dimension reduction in Euclidean spaces, that can map any dataset of points into dimension with low…

cs.DS2025

How fast can you find a good hypothesis?

Anders Aamand, Maryam Aliakbarpour, Justin Y. Chen +1

In the hypothesis selection problem, we are given sample and query access to finite set of candidate distributions (hypotheses), , and samples f…

cs.DB2025

Efficient Training-Free Online Routing for High-Volume Multi-LLM Serving

Fangzhou Wu, Sandeep Silwal

Increasing demand for Large Language Models (LLMs) services imposes substantial deployment and computation costs on providers. LLM routing offers a cost-efficient solution by direc…

cs.DS2025

Breaking the Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition

Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard +4

We study differentially private algorithms for graph cut sparsification, a fundamental problem in algorithms, privacy, and machine learning. While significant progress has been mad…

cs.DS2025

On the Structure of Replicable Hypothesis Testers

Anders Aamand, Maryam Aliakbarpour, Justin Y. Chen +2

A hypothesis testing algorithm is replicable if, when run on two different samples from the same distribution, it produces the same output with high probability. This notion, defin…