Copertina

A Ring-Based Distributed Algorithm for Learning High-Dimensional Bayesian Networks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Laborda, Jorge D., Torrijos, Pablo, Puerta, José M., Gámez, José A.
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A Ring-Based Distributed Algorithm for Learning High-Dimensional Bayesian Networks
di: Laborda Sicilia, Jorge Daniel, et al.
Pubblicazione: (2023)

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search
di: Laborda, Jorge D., et al.
Pubblicazione: (2025)

FedGES: A Federated Learning Approach for BN Structure Learning
di: Torrijos, Pablo, et al.
Pubblicazione: (2025)

Bayesian Network Structural Consensus via Greedy Min-Cut Analysis
di: Torrijos, Pablo, et al.
Pubblicazione: (2025)

Federated Learning with Discriminative Naive Bayes Classifier
di: Torrijos, Pablo, et al.
Pubblicazione: (2025)

ODTE -- An ensemble of multi-class SVM-based oblique decision trees
di: Montañana, Ricardo, et al.
Pubblicazione: (2024)

Comparison of High-Dimensional Bayesian Optimization Algorithms on BBOB
di: Santoni, Maria Laura, et al.
Pubblicazione: (2023)

Understanding High-Dimensional Bayesian Optimization
di: Papenmeier, Leonard, et al.
Pubblicazione: (2025)

Estimation of Distribution Algorithms with Matrix Transpose in Bayesian Learning
di: Kim, Dae-Won, et al.
Pubblicazione: (2024)

From Sorting Algorithms to Scalable Kernels: Bayesian Optimization in High-Dimensional Permutation Spaces
di: Xie, Zikai, et al.
Pubblicazione: (2025)

A Full DAG Score-Based Algorithm for Learning Causal Bayesian Networks with Latent Confounders
di: Gonzales, Christophe, et al.
Pubblicazione: (2024)

Scalable Structure Learning of Bayesian Networks by Learning Algorithm Ensembles
di: Liu, Shengcai, et al.
Pubblicazione: (2025)

A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis
di: Urban, Christopher J., et al.
Pubblicazione: (2020)

An Adaptive Dropout Approach for High-Dimensional Bayesian Optimization
di: Huang, Jundi, et al.
Pubblicazione: (2025)

RLBayes: a Bayesian Network Structure Learning Algorithm via Reinforcement Learning-Based Search Strategy
di: Wang, Mingcan, et al.
Pubblicazione: (2025)

Generative Adversarial Networks for High-Dimensional Item Factor Analysis: A Deep Adversarial Learning Algorithm
di: Luo, Nanyu, et al.
Pubblicazione: (2025)

Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization
di: Xu, Zhitong, et al.
Pubblicazione: (2024)

Unleashing the Potential of Acquisition Functions in High-Dimensional Bayesian Optimization
di: Zhao, Jiayu, et al.
Pubblicazione: (2023)

High Dimensional Bayesian Optimization using Lasso Variable Selection
di: Hoang, Vu Viet, et al.
Pubblicazione: (2025)

We Still Don't Understand High-Dimensional Bayesian Optimization
di: Doumont, Colin, et al.
Pubblicazione: (2025)

Robust Sparse Bayesian Learning Based on Minimum Error Entropy for Noisy High-Dimensional Brain Activity Decoding
di: Li, Yuanhao, et al.
Pubblicazione: (2025)

Navigating in High-Dimensional Search Space: A Hierarchical Bayesian Optimization Approach
di: Li, Wenxuan, et al.
Pubblicazione: (2024)

A Resampling-Based Framework for Network Structure Learning in High-Dimensional Data
di: Huang, Ziwei, et al.
Pubblicazione: (2026)

Adaptive-Distribution Randomized Neural Networks for PDEs: A Low-Dimensional Distribution-Learning Framework
di: Yang, You, et al.
Pubblicazione: (2026)

A Federated Random Forest Solution for Secure Distributed Machine Learning
di: Cotorobai, Alexandre, et al.
Pubblicazione: (2025)

Bayesian Active Learning By Distribution Disagreement
di: Werner, Thorben, et al.
Pubblicazione: (2025)

High-Dimensional Bayesian Optimization via Random Projection of Manifold Subspaces
di: Nguyen, Quoc-Anh Hoang, et al.
Pubblicazione: (2024)

HypeMARL: Multi-Agent Reinforcement Learning For High-Dimensional, Parametric, and Distributed Systems
di: Botteghi, Nicolò, et al.
Pubblicazione: (2025)

Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces
di: Papenmeier, Leonard, et al.
Pubblicazione: (2023)

Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization
di: Tran-The, Hung, et al.
Pubblicazione: (2019)

Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization
di: Bardou, Anthony, et al.
Pubblicazione: (2023)

Computationally Efficient High-Dimensional Bayesian Optimization via Variable Selection
di: Shen, Yihang, et al.
Pubblicazione: (2021)

Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm
di: Lu, Miao, et al.
Pubblicazione: (2024)

Safe Bayesian Optimization for the Control of High-Dimensional Embodied Systems
di: Wei, Yunyue, et al.
Pubblicazione: (2024)

Expected Coordinate Improvement for High-Dimensional Bayesian Optimization
di: Zhan, Dawei
Pubblicazione: (2024)

EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization
di: Cheon, Mujin, et al.
Pubblicazione: (2024)

More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms
di: Zakerinia, Hossein, et al.
Pubblicazione: (2024)

A Distributional View of High Dimensional Optimization
di: Benning, Felix
Pubblicazione: (2025)

Learning High-Dimensional Parity Functions with Product Networks using Gradient Descent
di: Larue, Guillaume, et al.
Pubblicazione: (2026)

Leveraging Axis-Aligned Subspaces for High-Dimensional Bayesian Optimization with Group Testing
di: Hellsten, Erik, et al.
Pubblicazione: (2025)