Optimal Clustering in Stable Instances Using Combinations of Exact and Noisy Ordinal Queries

This work studies clustering algorithms which operates with <i>ordinal</i> or <i>comparison-based</i> queries (operations), a situation that arises in many active-learning applications where “dissimilarities” between data points are evaluated by humans. Typically, <i>ex...

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Bibliographic Details
Main Authors: Enrico Bianchi, Paolo Penna
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Algorithms
Subjects:
Online Access:https://www.mdpi.com/1999-4893/14/2/55