4 citations · 5 across the 2 of their papers we have counts for
3 papers
cs.LG2020★ 1 cited
Impact of Community Structure on Consensus Machine Learning
Bao Huynh, Haimonti Dutta, Dane Taylor
Consensus dynamics support decentralized machine learning for data that is distributed across a cloud compute cluster or across the internet of things. In these and other settings,…
stat.ME2019★ 4 cited
Estimation and Feature Selection in Mixtures of Generalized Linear Experts Models
Bao Tuyen Huynh, Faicel Chamroukhi
Mixtures-of-Experts (MoE) are conditional mixture models that have shown their performance in modeling heterogeneity in data in many statistical learning approaches for prediction,…
stat.ML2018
Regularized Maximum Likelihood Estimation and Feature Selection in Mixtures-of-Experts Models
Faicel Chamroukhi, Bao-Tuyen Huynh
Mixture of Experts (MoE) are successful models for modeling heterogeneous data in many statistical learning problems including regression, clustering and classification. Generally…