For two-color data, the paper provides the first constant-factor approximation algorithms for closest fair clustering and for fair consensus clustering under the generalized mean objective.
Proof:Without loss of generality, assume thatx 1 ≤x 2 ≤ · · · ≤xt
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Towards Fair Representation: Clustering and Consensus
For two-color data, the paper provides the first constant-factor approximation algorithms for closest fair clustering and for fair consensus clustering under the generalized mean objective.