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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.

168,657 papers · 148 categories

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2 results for “H-likelihood”

Deep Neural Networks for Semiparametric Frailty Models via H-likelihoodstat.ML

Proposes a deep neural network for predicting clustered time-to-event data.

problem Predicting clustered time-to-event data with subject-specific frailties.

method Deep neural network based gamma frailty model (DNN-FM) trained using negative profiled h-likelihood.

result Enhances prediction performance compared to existing methods.

Deep learning Frailty models Time-to-event data H-likelihood Gamma distribution

2023-07-13abs ↗pdf ↗

Subject-specific Deep Neural Networks for Count Data with High-cardinality Categorical Featurescs.LG

Proposes a new DNN framework for count data with high-cardinality features.

problem Real-world data often have correlations and high-cardinality categorical features that traditional DNNs overlook.

method Introduces a hierarchical likelihood learning framework with gamma random effects for Poisson DNNs.

result Improves prediction performance by capturing nonlinear effects and subject-specific cluster effects.

Deep Neural Networks Count Data High-cardinality Features Gamma Random Effects Poisson DNN

2023-10-18abs ↗pdf ↗