We present a simple algorithm for clustering semantic patterns based on distributional similarity and use cluster memberships to guide semi-supervised pattern discovery. We apply ...
In this paper we consider the problem of describing the action being performed by human figures in still images. We will attack this problem using an unsupervised learning approac...
Greg Mori, Hao Jiang, Mark S. Drew, Yang Wang 0003...
Recently, many approaches have been proposed for visual object category detection. They vary greatly in terms of how much supervision is needed. High performance object detection m...
In this paper we investigate unsupervised population of a biomedical ontology via information extraction from biomedical literature. Relationships in text seldom connect simple ent...
Cartic Ramakrishnan, Pablo N. Mendes, Shaojun Wang...
This paper demonstrates how unsupervised techniques can be used to learn models of deep linguistic structure. Determining the semantic roles of a verb's dependents is an impo...