Locally adaptive regression splines

Multivariate Adaptive Regression Splines

Discussion: Multivariate Adaptive Regression Splines

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Spatially Adaptive Bayesian Regression Splines

In this paper we study penalized regression splines (P-splines), which are low–order basis function splines with a penalty to avoid undersmoothing. Such P–splines are typically not spatially adaptive, and hence can have trouble when functions are varying rapidly. While frequentist methods are available to address this issue, no Bayesian techniques have been developed. Our approach is to model t...

Locally Adaptive Subspace Regression

Incremental learning of sensorimotor transformations in high dimensional spaces is one of the basic prerequisites for the success of autonomous robot devices as well as biological movement systems. So far, due to sparsity of data in high dimensional spaces, learning in such settings requires a significant amount of prior knowledge about the learning task, usually provided by a human expert. In ...

Spatially Adaptive Bayesian Penalized Regression Splines (P-splines)

In this paper we study penalized regression splines (P-splines), which are low–order basis splines with a penalty to avoid undersmoothing. Such P–splines are typically not spatially adaptive, and hence can have trouble when functions are varying rapidly. Our approach is to model the penalty parameter inherent in the P–spline method as a heteroscedastic regression function. We develop a full Bay...