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.
New method speeds up sparse Bayesian learning without covariance matrix.
New method learns decisions from collective preferences without individual covariates.
We provide a theoretical treatment of over-specified Gaussian mixtures of experts with covariate-free gating networks. We establish the convergence rates of the maximum likelihood estimation (MLE) for these models. Our proof technique is based on a novel notion of \emph{algebraic independence} of the expert functions. …
A new model integrates covariates with grade of membership analysis for better latent structure recovery.