On-device research index

arXiv research

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.

169,341 papers · 148 categories

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3 results for “Rank-Likelihood”

Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihoodstat.ML

Bayesian model improves discriminative factor analysis for non-Gaussian data.

problem Discriminative factor analysis for non-Gaussian data.

method Introduces max-margin rank-likelihood and integrates it with linear Bayesian support vector machines. Extends to nonlinear case using mixtures of local linear classifiers.

result Superior performance demonstrated on benchmark and real data.

Bayesian Rank-Likelihood Max-Margin Support Vector Machines Dirichlet Processes

2015-04-28abs ↗pdf ↗

Identifiable Bayesian Deep Generative Copulas with Unknown Layer Widths for Data with Arbitrary Marginal Distributionsstat.ML

Identifies interpretable generative model for multivariate data.

problem Black-box architectures of deep generative models are often unidentified and difficult to interpret.

method Introduces Deep Discrete Encoder (DDE) Copula, a hierarchical binary latent variable model inside a copula framework.

result Establishes conditions for identification of DDE copula parameters and proves posterior consistency.

Bayesian deep generative models copulas latent variables multivariate data interpretability

2026-05-26abs ↗pdf ↗

Flexible sampling of discrete data correlations without the marginal distributionsstat.ML

Learning the joint dependence of discrete variables is a fundamental problem in machine learning, with many applications including prediction, clustering and dimensionality reduction. More recently, the framework of copula modeling has gained popularity due to its modular parametrization of joint distributions. Among o…

2013-06-12abs ↗pdf ↗