A fundamental assumption for any machine learning task is to have training and test data instances drawn from the same distribution while having a sufficiently large number of tra...
We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various concepts have been adapted to the MI representation. Howe...
This paper demonstrates two methods to improve the performance of instancebased learning (IBL) algorithms for the problem of Semantic Role Labeling (SRL). Two IBL algorithms are u...
In this paper, we propose a Relation Expansion framework, which uses a few seed sentences marked up with two entities to expand a set of sentences containing target relations. Duri...
Abstract--Rough face alignments lead to suboptimal performance of face identification systems. In this study, we present a novel approach for identifying genders from facial images...