The identification of a SISO linear dynamic system in the presence of output noise disturbances is studied. It is shown that a nonparametric model for the disturbing output noise ...
The goal of clustering is to identify distinct groups in a dataset. Compared to non-parametric clustering methods like complete linkage, hierarchical model-based clustering has th...
We introduce a novel approach for magnetic resonance image (MRI) brain tissue classification by learning image neighborhood statistics from noisy input data using nonparametric den...
Tolga Tasdizen, Suyash P. Awate, Ross T. Whitaker,...
We present a new method for multi-object segmentation in a maximum a posteriori estimation framework. Our method is motivated by the observation that neighboring or coupling objec...
In this paper we propose a novel clustering algorithm based on maximizing the mutual information between data points and clusters. Unlike previous methods, we neither assume the d...