Fetching the paper…
Reading the bibliography…
Model selection, via penalized likelihood type criteria, is a standard task in many statistical inference and machine learning problems.
Convergence Rates for Gaussian Mixtures of Experts
Ho, N., Yang, C.-Y., & Jordan, M. I. (2019) · 1907
Earlier work this paper cites.
Some Comments on CP
Mallows, C. L. (1973) · 1973
Earlier work this paper cites.
A new look at the statistical model identification
Akaike, H. (1974) · 1974
Earlier work this paper cites.
Estimating the dimension of a model
Schwarz, G. et al. (1978) · 1978
Earlier work this paper cites.
Adaptive Mixtures of Local Experts
Jacobs, R. A., Jordan, M. I., Nowlan, S. J., & Hinton, G. E. (1991) · 1991
Earlier work this paper cites.
Sliced Inverse Regression for Dimension Reduction
Li, K.-C. (1991) · 1991
Earlier work this paper cites.
Hierarchical mixtures of experts and the EM algorithm
Jordan, M. I. & Jacobs, R. A. (1994) · 1994
Earlier work this paper cites.
An Alternative Model for Mixtures of Experts
Xu, L., Jordan, M. I., & Hinton, G. E. (1995) · 1995
Earlier work this paper cites.
Structural adaptation in mixture of experts
Ramamurti, V. & Ghosh, J. (1996) · 1996
Earlier work this paper cites.
Weak Convergence and Empirical Processes: With Applications to Statistics Springer Series in Statistics
Van Der Vaart, A. & Wellner, J. (1996) · 1996
Earlier work this paper cites.
Minimum contrast estimators on sieves: exponential bounds and rates of convergence
Birgé, L., Massart, P., et al. (1998) · 1998
Earlier work this paper cites.
Use of localized gating in mixture of experts networks
Ramamurti, V. & Ghosh, J. (1998) · 1998
Earlier work this paper cites.
Molecular classification of cancer: class discovery and class prediction by gene expression monitoring
Golub, T. R., Slonim, D. K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J. P., Coller, H., Loh, M. L., Downing, J. R., Caligiuri, M. A., Bloomfield, C. D., & Lander, E. S. (1999) · 1999
Earlier work this paper cites.
Hierarchical mixtures-of-experts for exponential family regression models: approximation and maximum likelihood estimation
Jiang, W. & Tanner, M. A. (1999) · 1999
Earlier work this paper cites.
Classification using localized mixture of experts
Moerland, P. (1999) · 1999
Earlier work this paper cites.
Rates of convergence for the Gaussian mixture sieve
Genovese, C. R. & Wasserman, L. (2000) · 2000
Earlier work this paper cites.
On-line EM algorithm for the normalized gaussian network
Sato, M. & Ishii, S. (2000) · 2000
Earlier work this paper cites.
Tumor classification by partial least squares using microarray gene expression data
Nguyen, D. V. & Rocke, D. M. (2002) · 2002
Cited alongside, same era.
Localised mixtures of experts for mixture of regressions
Bouchard, G. (2003) · 2003
Cited alongside, same era.
Concentration Inequalities and Model Selection: Ecole d’Eté de Probabilités de Saint-Flour XXXIII-2003
Massart, P. (2007) · 2003
Cited alongside, same era.
Minimal penalties for Gaussian model selection
Birgé, L. & Massart, P. (2007) · 2007
Cited alongside, same era.
Introduction to Empirical Processes and Semiparametric Inference
Kosorok, M. R. (2007) · 2007
Cited alongside, same era.
The MDL principle, penalized likelihoods, and statistical risk
Barron, A. R., Huang, C., Li, J., & Luo, X. (2008) · 2008
Cited alongside, same era.
Twenty Years of Mixture of Experts
Yuksel, S. E., Wilson, J. N., & Gader, P. D. (2012) · 2012
Later among the works it cites.
Convergence of latent mixing measures in finite and infinite mixture models
Nguyen, X. et al. (2013) · 2013
Later among the works it cites.
Mixture of Gaussian regressions model with logistic weights, a penalized maximum likelihood approach
Montuelle, L., Le Pennec, E., et al. (2014) · 2014
Later among the works it cites.
Posterior consistency in conditional density estimation by covariate dependent mixtures
Norets, A. & Pelenis, J. (2014) · 2014
Later among the works it cites.
A Universal Approximation Theorem for Mixture-of-Experts Models
Nguyen, H. D., Lloyd-Jones, L. R., & McLachlan, G. J. (2016) · 2016
Later among the works it cites.
Nonlinear network-based quantitative trait prediction from transcriptomic data
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
A sparse PLS for variable selection when integrating omics data
Lê Cao, K.-A., Rossouw, D., Robert-Granié, C., & Besse, P. (2008) · 2008
Cited alongside, same era.
Approximation of probability density functions via location-scale finite mixtures in Lebesgue spaces
Nguyen, T., Chamroukhi, F., Nguyen, H. D., & McLachlan, G. J. (2020b) · 2008
Cited alongside, same era.
New estimation and feature selection methods in mixture-of-experts models
Khalili, A. (2010) · 2010
Cited alongside, same era.
Approximation of conditional densities by smooth mixtures of regressions
Norets, A. et al. (2010) · 2010
Cited alongside, same era.
Conditional density estimation by penalized likelihood model selection and applications
Cohen, S. & Pennec, E. L. (2011) · 2011
Cited alongside, same era.
The Lasso as an
Massart, P. & Meynet, C. (2011) · 2011
Cited alongside, same era.
Devijver, E., Gallopin, M., & Perthame, E. (2017) · 2017
Later among the works it cites.
Deep mixture of linear inverse regressions applied to head-pose estimation
Lathuilière, S., Juge, R., Mesejo, P., Muñoz-Salinas, R., & Horaud, R. (2017) · 2017
Later among the works it cites.
Adaptive Bayesian estimation of conditional densities
Norets, A. & Pati, D. (2017) · 2017
Later among the works it cites.
Block-Diagonal Covariance Selection for High-Dimensional Gaussian Graphical Models
Devijver, E. & Gallopin, M. (2018) · 2018
Later among the works it cites.
Practical and theoretical aspects of mixture-of-experts modeling: An overview
Nguyen, H. D. & Chamroukhi, F. (2018) · 2018
Later among the works it cites.
Inverse regression approach to robust nonlinear high-to-low dimensional mapping
Perthame, E., Forbes, F., & Deleforge, A. (2018) · 2018
Later among the works it cites.
Minimal penalties and the slope heuristics: a survey
Arlot, S. (2019) · 2019
Later among the works it cites.
Regularized Estimation and Feature Selection in Mixtures of Gaussian-Gated Experts Models
Chamroukhi, F., Lecocq, F., & Nguyen, H. D. (2019) · 2019
Later among the works it cites.
Approximation results regarding the multiple-output Gaussian gated mixture of linear experts model
Nguyen, H. D., Chamroukhi, F., & Forbes, F. (2019) · 2019
Later among the works it cites.
Model selection and multi-model inference
Anderson, D. & Burnham, K. (2004) · 2020
Later among the works it cites.
A non-asymptotic penalization criterion for model selection in mixture of experts models
Nguyen, T. T., Nguyen, H. D., Chamroukhi, F., & Forbes, F. (2021) · 2021
Closest in time.