A non-asymptotic approach for model selection via penalization in
high-dimensional mixture of experts models

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A non-asymptotic approach for model selection via penalization in high-dimensional mixture of experts models

6 April 2021

TrungTin Nguyen

Faicel Chamroukhi

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Papers citing "A non-asymptotic approach for model selection via penalization in high-dimensional mixture of experts models"

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Title
Model Selection for Gaussian-gated Gaussian Mixture of Experts Using Dendrograms of Mixing Measures Tuan Thai TrungTin Nguyen Dat Do Nhat Ho Christopher Drovandi 188 0 0 19 May 2025
Mixture of partially linear experts Yeongsan Hwang Byungtae Seo Sangkon Oh 54 0 0 05 May 2024
Risk Bounds for Mixture Density Estimation on Compact Domains via the $h$ -Lifted Kullback--Leibler Divergence Mark Chiu Chong Hien Nguyen TrungTin Nguyen 52 1 0 19 Apr 2024
CompeteSMoE -- Effective Training of Sparse Mixture of Experts via Competition Quang Pham Giang Do Huy Nguyen TrungTin Nguyen Chenghao Liu ... Binh T. Nguyen Savitha Ramasamy Xiaoli Li Steven C. H. Hoi Nhat Ho 63 20 0 04 Feb 2024
Distributed Learning of Mixtures of Experts Faicel Chamroukhi Nhat-Thien Pham FedML 12 0 0 15 Dec 2023
Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts Huy Nguyen TrungTin Nguyen Khai Nguyen Nhat Ho MoE 105 14 0 12 May 2023
PanIC: consistent information criteria for general model selection problems Hien Nguyen 24 2 0 07 Mar 2023
Non-asymptotic oracle inequalities for the Lasso in high-dimensional mixture of experts TrungTin Nguyen Hien Nguyen Faicel Chamroukhi Geoffrey J. McLachlan 65 2 0 22 Sep 2020