- AI · arxiv/cs.LG · 8 min
Admissible Objectives for Hierarchical Clustering Formally Characterized
Tsukuba and Ando extend the theory of objective functions for hierarchical clustering, characterizing when functions recover ground-truth structures and introducing max-type variants.
April 28, 2026 Read → → - AI · arxiv/cs.AI · 5 min
Fast Entropic Approximations cut entropy computation by 37x
Horenko et al. propose non-singular rational approximations of Shannon entropy and KL divergence that preserve mathematical properties while reducing computation cost and improving ML model training.
April 27, 2026 Read → → - AI · arxiv/cs.LG · 8 min
Chromatic Clustering Requires New Algorithms to Match Standard Performance
Adding color constraints to correlation clustering increases computational difficulty; a new coupled approach recovers optimal approximation bounds.
April 20, 2026 Read → →