A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Researchers prove NP-hardness of learning parameter-bounded Bayes nets.
Sharp bounds on hyperbolic metrics in Ptolemaic spaces are derived.
Information that is stored in an encrypted format is, by definition, usually not amenable to statistical analysis or machine learning methods. In this paper we present detailed analysis of coordinate and accelerated gradient descent algorithms which are capable of fitting least squares and penalised ridge regression mo…
Two approaches improve parameter learning in various mixture models.
This paper analyzes a time-dependent CFMM called RMM-01, focusing on its pricing and stability.
Lower bounds on Bayes risk for realizable models derived using information theory.
New IDS algorithm refines parameter norm bounds for better bandit performance.
Generative operators solve many convex problems with minimal parameters.
Develops efficient method for updating models with small data changes.