In this paper, we examine the problem of learning from noisecontaminated data in high-dimensional space. A new learning approach based on projections onto multi-dimensional ellips...
In this paper, we present a novel entropy estimator for a given set of samples drawn from an unknown probability density function (PDF). Counter to other entropy estimators, the e...
We present a methodology for enhancing the delivery of usergenerated content in online social networks. To this end, we first regularize the social graph via node capacity and li...
The goal of the work described here is to limit the computation needed in unit selection Viterbi search for text-to-speech synthesis. The broader goal is to improve speech quality...
This paper considers the problem of joint blind source separation (J-BSS), which appears in many practical problems such as blind deconvolution or functional magnetic resonance im...