We investigate ways in which an algorithm can improve its expected performance by fine-tuning itself automatically with respect to an arbitrary, unknown input distribution. We gi...
Nir Ailon, Bernard Chazelle, Kenneth L. Clarkson, ...
An active learner has a collection of data points, each with a label that is initially hidden but can be obtained at some cost. Without spending too much, it wishes to find a cla...
This paper presents an improved distance measure for speaker clustering in speaker diarization systems. The proposed phonetic subspace mixture (PSM) model introduces phonetic info...
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Modeling data by multiple low-dimensional planes is an important problem in many applications such as computer vision and pattern recognition. In the most general setting where on...