4 citations · 8 across the 11 of their papers we have counts for
4 papers · 1 filter
Bayesian Network Structural Consensus via Greedy Min-Cut Analysis
Pablo Torrijos, José M. Puerta, Juan A. Aledo +1
This paper presents the Min-Cut Bayesian Network Consensus (MCBNC) algorithm, a greedy method for structural consensus of Bayesian Networks (BNs), with applications in federated le…
FedGES: A Federated Learning Approach for BN Structure Learning
Pablo Torrijos, José A. Gámez, José M. Puerta
Bayesian Network (BN) structure learning traditionally centralizes data, raising privacy concerns when data is distributed across multiple entities. This research introduces Federa…
Federated Learning with Discriminative Naive Bayes Classifier
Pablo Torrijos, Juan C. Alfaro, José A. Gámez +1
Federated Learning has emerged as a promising approach to train machine learning models on decentralized data sources while preserving data privacy. This paper proposes a new feder…
Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search
Jorge D. Laborda, Pablo Torrijos, José M. Puerta +1
This article presents MCTS-BN, an adaptation of the Monte Carlo Tree Search (MCTS) algorithm for the structural learning of Bayesian Networks (BNs). Initially designed for game tre…