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20242026
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cs.DS2026

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.DS2026

Adversarially Robust Approximate Furthest Neighbor

Kiarash Banihashem, Jeff Giliberti, Prashant Gokhale +5

We work in the adaptive query model, where one is given a point set and seeks to construct a data structure that can answer correctly and efficiently a seq…

cs.DS2026

Skirting Additive Error Barriers for Private Turnstile Streams

Anders Aamand, Justin Y. Chen, Sandeep Silwal

We study differentially private continual release of the number of distinct items in a turnstile stream, where items may be both inserted and deleted. A recent work of Jain, Kalema…

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

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…