Cover Image

The MELODIC family for simultaneous binary logistic regression in a reduced space

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	de Rooij, Mark, Groenen, Patrick J. F.
Format:	Preprint
Published:	2021
Subjects:	Methodology Computation Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Variational empirical Bayes variable selection in high-dimensional logistic regression
by: Tang, Yiqi, et al.
Published: (2025)

Discriminative classification with generative features: bridging Naive Bayes and logistic regression
by: Terner, Zachary, et al.
Published: (2025)

Statistical inference for case-control logistic regression via integrating external summary data
by: Shi, Hengchao, et al.
Published: (2024)

Optimal and computationally tractable lower bounds for logistic log-likelihoods
by: Anceschi, Niccolò, et al.
Published: (2024)

Approximate Bayesian inference for cumulative probit regression models
by: Aliverti, Emanuele
Published: (2025)

Gradient-based optimization for variational empirical Bayes multiple regression
by: Banerjee, Saikat, et al.
Published: (2024)

Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression
by: Ascolani, Filippo, et al.
Published: (2025)

On metric choice in dimension reduction for Fréchet regression
by: Soale, Abdul-Nasah, et al.
Published: (2024)

Guiding adaptive shrinkage by co-data to improve regression-based prediction and feature selection
by: van de Wiel, Mark A., et al.
Published: (2024)

Fréchet random forests for metric space valued regression with non euclidean predictors
by: Capitaine, Louis, et al.
Published: (2019)

Imputation of missing values in multi-view data
by: van Loon, Wouter, et al.
Published: (2022)

Calibration of P-values for calibration and for deviation of a subpopulation from the full population
by: Tygert, Mark
Published: (2022)

Dimension-reduced Reconstruction Map Learning for Parameter Estimation in Likelihood-Free Inference Problems
by: Zhang, Rui, et al.
Published: (2024)

Monte Carlo inference for semiparametric Bayesian regression
by: Kowal, Daniel R., et al.
Published: (2023)

View selection in multi-view stacking: Choosing the meta-learner
by: van Loon, Wouter, et al.
Published: (2020)

Cross-validation for change-point regression: pitfalls and solutions
by: Pein, Florian, et al.
Published: (2021)

Barycentric model aggregation in the Wasserstein space of distributions and a variational approach to consistency
by: Androulakis, Emmanouil, et al.
Published: (2025)

Downscaling land surface temperature data using edge detection and block-diagonal Gaussian process regression
by: Dandapanthula, Sanjit, et al.
Published: (2026)

A Multinomial Canonical Decomposition Model, with emphasis on the analysis of Multivariate Binary data
by: de Rooij, Mark
Published: (2024)

A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression
by: Kim, Youngseok, et al.
Published: (2022)

Fast approximative estimation of conditional Shapley values when using a linear regression model or a polynomial regression model
by: Aanes, Fredrik Lohne
Published: (2025)

Bayesian Federated Inference for regression models based on non-shared multicenter data sets from heterogeneous populations
by: Jonker, Marianne A, et al.
Published: (2024)

A proposal for PU classification under Non-SCAR using clustering and logistic model
by: Furmanczyk, Konrad, et al.
Published: (2026)

Estimating equations for survival analysis with pooled logistic regression
by: Zivich, Paul N, et al.
Published: (2025)

Network-based Neighborhood regression
by: Zhen, Yaoming, et al.
Published: (2024)

Progression: an extrapolation principle for regression
by: Buriticá, Gloria, et al.
Published: (2024)

Provably robust learning of regression neural networks using $β$-divergences
by: Ghosh, Abhik, et al.
Published: (2026)

Efficient posterior sampling for high-dimensional imbalanced logistic regression
by: Sen, Deborshee, et al.
Published: (2019)

Semi-supervised learning for linear extremile regression
by: Jiang, Rong, et al.
Published: (2025)

Biarchetype analysis: simultaneous learning of observations and features based on extremes
by: Alcacer, Aleix, et al.
Published: (2023)

Adaptive group-regularized logistic elastic net regression
by: Münch, Magnus M., et al.
Published: (2018)

Convex estimation of Gaussian graphical regression models with covariates
by: Liu, Ruobin, et al.
Published: (2024)

Neural interval-censored survival regression with feature selection
by: Meixide, Carlos García, et al.
Published: (2022)

Performance of models for monitoring sustainable development goals from remote sensing: A three-level meta-regression
by: Klingwort, Jonas, et al.
Published: (2026)

A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC
by: Llorente, F., et al.
Published: (2021)

Outrigger local polynomial regression
by: Young, Elliot H., et al.
Published: (2026)

flexBART: Flexible Bayesian regression trees with categorical predictors
by: Deshpande, Sameer K.
Published: (2022)

A semi-supervised learning using over-parameterized regression
by: Hagiwara, Katsuyuki
Published: (2024)

Personalizing black-box models for nonparametric regression with minimax optimality
by: Li, Sai, et al.
Published: (2026)

Wasserstein F-tests for Fréchet regression on Bures-Wasserstein manifolds
by: Xu, Haoshu, et al.
Published: (2024)