activity
20242026
most citedDataset Dictionary Learning in a Wasserstein Space for Federated Domain Adaptation

1 citations · 1 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2026

DeFed-GMM-DaDiL: A Decentralized Federated Framework for Domain Adaptation

Rebecca Clain, Eduardo Fernandes Montesuma, Fred Ngole Mboula

Decentralized multi-source domain adaptation seeks to transfer knowledge from multiple heterogeneous and related source domains to an unlabeled target domain in a decentralized set…

cs.LG2026

On the Role of DAG topology in Energy-Aware Cloud Scheduling : A GNN-Based Deep Reinforcement Learning Approach

Anas Hattay, Fred Ngole Mboula, Eric Gascard +1

Cloud providers must assign heterogeneous compute resources to workflow DAGs while balancing competing objectives such as completion time, cost, and energy consumption. In this wor…

cs.LG2025

Decentralized Federated Dataset Dictionary Learning for Multi-Source Domain Adaptation

Rebecca Clain, Eduardo Fernandes Montesuma, Fred Ngolè Mboula

Decentralized Multi-Source Domain Adaptation (DMSDA) is a challenging task that aims to transfer knowledge from multiple related and heterogeneous source domains to an unlabeled ta…

stat.ML2025

Unsupervised Anomaly Detection through Mass Repulsing Optimal Transport

Eduardo Fernandes Montesuma, Adel El Habazi, Fred Ngole Mboula

Detecting anomalies in datasets is a longstanding problem in machine learning. In this context, anomalies are defined as a sample that significantly deviates from the remaining dat…

cs.LG2024

Online Multi-Source Domain Adaptation through Gaussian Mixtures and Dataset Dictionary Learning

Eduardo Fernandes Montesuma, Stevan Le Stanc, Fred Ngolè Mboula

This paper addresses the challenge of online multi-source domain adaptation (MSDA) in transfer learning, a scenario where one needs to adapt multiple, heterogeneous source domains…

cs.LG2024★ 1 cited

Dataset Dictionary Learning in a Wasserstein Space for Federated Domain Adaptation

Eduardo Fernandes Montesuma, Fabiola Espinoza Castellon, Fred Ngolè Mboula +3

Multi-Source Domain Adaptation (MSDA) is a challenging scenario where multiple related and heterogeneous source datasets must be adapted to an unlabeled target dataset. Conventiona…