Abstract. We propose a novel unsupervised transfer learning framework that utilises unlabelled auxiliary data to quantify and select the most relevant transferrable knowledge for r...
We introduce a novel approach to incremental e-mail categorization based on identifying and exploiting "clumps" of messages that are classified similarly. Clumping reflec...
Abstract--Sensor networks can benefit greatly from locationawareness, since it allows information gathered by the sensors to be tied to their physical locations. Ultra-wide bandwid...
Totally asynchronous code-division multiple-access (CDMA) systems are addressed. In part I, the fundamental limits of asynchronous CDMA systems were analyzed in terms of total cap...
We propose an informative dialect recognition system that learns phonetic transformation rules, and uses them to identify dialects. A hidden Markov model is used to align referenc...
Nancy F. Chen, Wade Shen, Joseph P. Campbell, Pedr...