The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
In this paper, we present CONTRAlign, an extensible and fully automatic framework for parameter learning and protein pairwise sequence alignment using pair conditional random field...
The goal of this work is to automatically learn a large
number of British Sign Language (BSL) signs from TV
broadcasts. We achieve this by using the supervisory information
avai...
Patrick Buehler (University of Oxford), Mark Everi...
Background: Certain protein families are highly conserved across distantly related organisms and belong to large and functionally diverse superfamilies. The patterns of conservati...
Abstract. In this paper we introduce a novel approach for learning view-invariant gait representation that does not require synthesizing particular views or any camera calibration....