One way to obtain an intuitive understanding of the wavelet transform is to explain it in terms
of segmentation of the time-frequency/scale domain. The ordinary Fourier transform does …

The regression estimation problem has a long history. Already in 1632 Galileo Galilei used a
procedure which can be interpreted as? tting a linear relationship to contaminated observed …

We study what we call" dyadic CART"--a method of nonparametric regression which
constructs a recursive partition by optimizing a complexity penalized sum of squares, where …

We propose a new method of nonparametric estimation which is based on locally constant
smoothing with an adaptive choice of weights for every pair of data points. Some theoretical …

The vision of researchers to create smart environments through the deployment of
thousands of sensors, each with a short range wireless communications channel and …

Since their inception in the 1980s, regression trees have been one of the more widely used
nonparametric prediction methods. Tree-structured methods yield a histogram …

The performance of the classification and regression trees (CART) pruning algorithm and
the final discrete selection by test sample as a functional estimation procedure are …

I introduce a class of Bayesian multiscale models (BMSM's) for one-dimensional
inhomogeneous Poisson processes. The focus is on estimating the (discretized) intensity …

Since their inception in the 1980's, regression trees have been one of the more widely used
non-parametric prediction methods. Tree-structured methods yield a histogram …

The more a priori knowledge we encode into a signal processing algorithm, the better
performance we can expect. In this paper, we overview several approaches to capturing the …