Motivated by a problem of targeted advertising in social networks, we introduce and study a new model of online learning on labeled graphs where the graph is initially unknown and...
In machine learning, ensemble classifiers have been introduced for more accurate pattern classification than single classifiers. We propose a new ensemble learning method that emp...
Abstract. Rampart is a toolkit of protocols to facilitate the development of high-integrity services, i.e., distributed services that retain their availability and correctness desp...
We present context-sensitive Multiple Task Learning, or csMTL as a method of inductive transfer. It uses additional contextual inputs along with other input features when learning ...
Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA struc...