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