arXiv Machine Learning By Hadley Black, Kasper Green Larsen, Arya Mazumdar, Barna Saha, Geelon So

Actively Learning Halfspaces without Synthetic Data

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arXiv:2509. 20848v2 Announce Type: replace-cross Abstract: In the classic point location problem, one is given an arbitrary dataset $X \subset \mathbb{R}^d$ of $n$ points with query access to an unknown halfspace $f : \mathbb{R}^d \to \{0,1\}$, and the goal is to learn the label of every point in $X$.

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arXiv Machine Learning
Jul 14

Learning Partition Trees for Nearest Neighbor Search

arXiv:2607. 09909v1 Announce Type: cross Abstract: We study nearest neighbor search from the perspective of data-driven algorithm design: given a dataset $P \subset \mathbb{R}^d$ of size $n$ and sample access to a query distribution over $\mathbb{R}^d$, the goal is to learn a data structure optimized for queries drawn from that specific distribution.

By Sanjeev Khanna, Ashwin Padaki, Erik Waingarten