This paper presents a novel method for reducing the dimensionality of kernel spaces. Recently, to maintain the convexity of training, loglinear models without mixtures have been u...
We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in co...
In this paper we propose a novel integrated circuit and architectural level technique to reduce leakage power consumption in high performance cache memories using single Vt (trans...
In wireless communication systems, adaptive modulation and coding (AMC) is used to improve the downlink (DL) spectral efficiency by exploiting the underlying channel condition. Ho...
Abstract. Maximum likelihood (ML) is an increasingly popular optimality criterion for selecting evolutionary trees [Felsenstein 1981]. Finding optimal ML trees appears to be a very...