We introduce in this paper a new model, called Multiclass Sparse Bayesian Regression (MCBR), that, unlike classical alternatives, automatically adapts the ...

We introduce in this paper a new model, called Multiclass Sparse Bayesian Regression (MCBR), that, unlike classical alternatives, automatically adapts the ...

This approach, called Multi-Class. Sparse Bayesian Regression (MCBR), is thus an intermediate solution between BRR and ARD. It requires less parameters to ...

This approach opens new ways for understanding the mental representation of various perceptual and cogni- tive parameters, which can be regarded as the study of ...

Multiclass Sparse Bayesian Regression for fMRI-Based Prediction · Vincent Michel, Evelyn Eger, Christine Keribin, Bertrand Thirion · Send Feedback · BibTeX Record.

Oct 22, 2024 · Graphical model of Multiclass Sparse Bayesian Regression (MCBR). We denote by y ∈ ℝn the targets to be predicted and by X ∈ ℝn×p the set of ...

Jun 23, 2011 · MCBR consists in grouping features into several classes and then regularizing each class differently in order to apply an adaptive and efficient ...

We introduce in this paper a new model, called Multiclass Sparse Bayesian Regression (MCBR), that, unlike classical alternatives, automatically adapts the ...

We introduce in this paper a new model, called Multiclass Sparse Bayesian Regression (MCBR), that, unlike classical alternatives, automatically adapts the ...

MCBR consists in grouping features into several classes and then regularizing each class differently in order to apply an adaptive and efficient regularization.