- 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
Formalizing How Much Data Proves a Learning Model Right
Researchers formalize identifying information—the bits needed to confirm or reject a hypothesis—bridging information theory with practical sample complexity.
April 17, 2026 Read → →