Active Nearest-Neighbor Learning in Metric Spaces

被引：0

作者：

Kontorovich, Aryeh ^{[1
]}

Sabato, Sivan ^{[1
]}

Urner, Ruth ^{[2
]}

机构：

[1] Ben Gurion Univ Negev, Dept Comp Sci, IL-8499000 Beer Sheva, Israel

[2] York Univ, Lassonde Sch Engn, EECS Dept, Toronto, ON, Canada

来源：

JOURNAL OF MACHINE LEARNING RESEARCH | 2018年 / 18卷

基金：

以色列科学基金会;

关键词：

Nearest-neighbors; active learning; metric spaces; non-parametric learning; BOUNDS; RATES; CLASSIFICATION; COMPRESSION; CONVERGENCE; ALGORITHMS; ERROR;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We propose a pool-based non-parametric active learning algorithm for general metric spaces, called MArgin Regularized Metric Active Nearest Neighbor (MARM AN N), which outputs a nearest-neighbor classifier. We give prediction error guarantees that depend on the noisy-margin properties of the input sample, and are competitive with those obtained by previously proposed passive learners. We prove that the label complexity of MARM AN N is significantly lower than that of any passive learner with similar error guarantees. M AR M AN N is based on a generalized sample compression scheme, and a new label-efficient active model-selection procedure.

引用

页数：38

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