Imagen de Portada

An ADMM approach for multi-response regression with overlapping groups and interaction effects

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Asenso, Theophilus Quachie, Zucknick, Manuela
Formato:	Preprint
Publicado:	2023
Materias:	Methodology Quantitative Methods Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Integrating Multiple Data Sources with Interactions in Multi-Omics Using Cooperative Learning
por: D'Alessandro, Matteo, et al.
Publicado: (2024)

PliableBVS: A flexible Bayesian variable selection method for modeling interactions with mandatory modifying variables
por: Asenso, Theophilus Quachie, et al.
Publicado: (2026)

Interpretable (not just posthoc-explainable) heterogeneous survivor bias-corrected treatment effects for assignment of postdischarge interventions to prevent readmissions
por: Xia, Hongjing, et al.
Publicado: (2023)

BAMITA: Bayesian Multiple Imputation for Tensor Arrays
por: Jiang, Ziren, et al.
Publicado: (2024)

Deciphering interventional dynamical causality from non-intervention complex systems
por: Shi, Jifan, et al.
Publicado: (2024)

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics
por: Zhu, Haonan, et al.
Publicado: (2025)

Causal Representation Learning from Multimodal Biomedical Observations
por: Sun, Yuewen, et al.
Publicado: (2024)

Distributional bias compromises leave-one-out cross-validation
por: Austin, George I., et al.
Publicado: (2024)

Dynamic Vine Copulas: Detecting and Quantifying Time-Varying Higher-Order Interactions
por: Safaai, Houman, et al.
Publicado: (2026)

MMIL: A novel algorithm for disease associated cell type discovery
por: Craig, Erin, et al.
Publicado: (2024)

In-silico biological discovery with large perturbation models
por: Miladinovic, Djordje, et al.
Publicado: (2025)

Conformal Prediction Under Feedback Covariate Shift for Biomolecular Design
por: Fannjiang, Clara, et al.
Publicado: (2022)

Scalable branch-and-bound model selection with non-monotonic criteria including AIC, BIC and Mallows's $\mathit{C_p}$
por: Vanhoefer, Jakob, et al.
Publicado: (2025)

Machine learning approaches for interpretable antibody property prediction using structural data
por: Michalewicz, Kevin, et al.
Publicado: (2025)

Prediction of good reaction coordinates and future evolution of MD trajectories using Regularized Sparse Autoencoders: A novel deep learning approach
por: Gupta, Abhijit
Publicado: (2022)

Probabilistic Joint and Individual Variation Explained (ProJIVE) for Data Integration
por: Murden, Raphiel J., et al.
Publicado: (2026)

Data-Driven Switchback Experiments: Theoretical Tradeoffs and Empirical Bayes Designs
por: Xiong, Ruoxuan, et al.
Publicado: (2024)

Estimating Treatment Effect under Additive Hazards Models with High-dimensional Covariates
por: Hou, Jue, et al.
Publicado: (2019)

Deconstructing Intraocular Pressure: A Non-invasive Multi-Stage Probabilistic Inverse Framework
por: Jaher, Md Rezwan, et al.
Publicado: (2025)

A non-parametric optimal design algorithm for population pharmacokinetics
por: Hovd, Markus, et al.
Publicado: (2025)

Nonparametric learning of covariate-based Markov jump processes using RKHS techniques
por: Han, Yuchen, et al.
Publicado: (2025)

Interpolation pour l'augmentation de donnees : Application à la gestion des adventices de la canne a sucre a la Reunion
por: Ferber, Frederick Fabre, et al.
Publicado: (2025)

A nonparametric approach to practical identifiability of nonlinear mixed effects models
por: Cassidy, Tyler, et al.
Publicado: (2025)

Socrates-Mol: Self-Oriented Cognitive Reasoning through Autonomous Trial-and-Error with Empirical-Bayesian Screening for Molecules
por: Wang, Xiangru, et al.
Publicado: (2025)

High-dimensional Many-to-many-to-many Mediation Analysis
por: Nguyen, Tien Dat, et al.
Publicado: (2026)

An efficient solution to Hidden Markov Models on trees with coupled branches
por: Vafa, Farzan, et al.
Publicado: (2024)

A Weighted U Statistic for Genetic Association Analyses of Sequencing Data
por: Wei, Changshuai, et al.
Publicado: (2015)

Controlling False Discovery in Arbitrarily Structured Hypothesis Spaces via Reproducing Kernels
por: Perets, Binyamin, et al.
Publicado: (2026)

Diagnosing overdispersion in longitudinal analyses with grouped nominal polytomous data
por: Salvador, Maria Letícia, et al.
Publicado: (2024)

BSD: a Bayesian framework for parametric models of neural spectra
por: Medrano, Johan, et al.
Publicado: (2024)

Calibeating Prediction-Powered Inference
por: van der Laan, Lars, et al.
Publicado: (2026)

Integrating Multiple Data Sources With Interactions in Multi‐Omics Using Cooperative Learning
por: Matteo D'Alessandro, et al.
Publicado: (2025)

Prediction of causal genes at GWAS loci with pleiotropic gene regulatory effects using sets of correlated instrumental variables
por: Khan, Mariyam, et al.
Publicado: (2024)

Multilevel testing of constraints induced by structural equation modeling in fMRI effective connectivity analysis: A proof of concept
por: Marrelec, G., et al.
Publicado: (2024)

A proxy-based approach for unmeasured confounding in electronic health records research
por: Kottler, Haley Colgate, et al.
Publicado: (2025)

Evaluating the effects of high-throughput structural neuroimaging predictors on whole-brain functional connectome outcomes via network-based vector-on-matrix regression
por: Lu, Tong, et al.
Publicado: (2023)

A latent factor approach to hyperspectral time series data for multivariate genomic prediction of grain yield in wheat
por: Kunst, Jonathan F., et al.
Publicado: (2026)

Lagged coherence: explicit and testable definition
por: Pascual-Marqui, Roberto D., et al.
Publicado: (2023)

Negative Spillover: A Potential Source of Bias in Pragmatic Clinical Trials
por: Mann, Sean
Publicado: (2023)

Realizing Common Random Numbers: Event-Keyed Hashing for Causally Valid Stochastic Models
por: Buffalo, Vince, et al.
Publicado: (2026)