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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.

168,742 papers · 148 categories

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3 results for “EM-Lasso”

Functional Mixtures-of-Expertsstat.ME

New functional ME models for predicting heterogeneous functional data.

problem Statistical analysis of heterogeneous functional data for prediction.

method Functional Mixtures-of-Experts (FME) models with Lasso-like regularization for sparsity.

result Accurate capture of complex nonlinear relationships and clustering of heterogeneous regression data.

functional data analysis heterogeneous data Mixtures-of-Experts Lasso regularization EM-Lasso

2022-02-04abs ↗pdf ↗

Functional mixture-of-experts for classificationstat.ML

Develops a functional mix-of-experts model for multiclass classification.

problem Multiclass classification with univariate functional predictors.

method Functional mix-of-experts model with regularization and sparsity constraints.

result Regularized maximum likelihood estimation yields interpretable coefficient functions.

functional data classification mix-of-experts regularization sparsity

2022-02-28abs ↗pdf ↗

Regularized Estimation and Feature Selection in Mixtures of Gaussian-Gated Experts Modelsstat.ML

Mixtures-of-Experts models and their maximum likelihood estimation (MLE) via the EM algorithm have been thoroughly studied in the statistics and machine learning literature. They are subject of a growing investigation in the context of modeling with high-dimensional predictors with regularized MLE. We examine MoE with …

2019-09-12abs ↗pdf ↗