Distance metric learning and nonlinear dimensionality reduction are two interesting and active topics in recent years. However, the connection between them is not thoroughly studi...
Clustering performance can often be greatly improved by
leveraging side information. In this paper, we consider constrained
clustering with pairwise constraints, which specify
s...
We consider a framework for semi-supervised learning using spectral decomposition-based unsupervised kernel design. We relate this approach to previously proposed semi-supervised l...
We consider the problem of learning mixtures of distributions via spectral methods and derive a tight characterization of when such methods are useful. Specifically, given a mixt...
An analog VLSI circuit used to model spectral shape analysis in the central auditory system is presented. Like the receptive fields of visual cortical neurons, the spectral respon...