Recent research has revealed that circularity (or, propriety) of complex random signals can be exploited in developing optimal signal processors. In this paper, a robust estimator...
Active selection of good training examples is an important approach to reducing data-collection costs in machine learning; however, most existing methods focus on maximizing classi...
Prem Melville, Stewart M. Yang, Maytal Saar-Tsecha...
Cache behavior modeling is an important part of modern optimizing compilers. In this paper we present a method to estimate the number of cache misses, at compile time, using a mac...
This paper derives a near optimal distributed Kalman filter to estimate a large-scale random field monitored by a network of N sensors. The field is described by a sparsely con...
This paper is concerned with the estimation of steganographic capacity in digital images, using information theoretic bounds and very large-scale experiments to approximate the dis...