We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
Probabilistic grammars offer great flexibility in modeling discrete sequential data like natural language text. Their symbolic component is amenable to inspection by humans, while...
In this paper we learn a dissimilarity measure for categorical data, for effective classification of the data points. Each categorical feature (with values taken from a finite set...
Jierui Xie, Boleslaw K. Szymanski, Mohammed J. Zak...
We consider a recently proposed optimization formulation of multi-task learning based on trace norm regularized least squares. While this problem may be formulated as a semidefini...
Ting Kei Pong, Paul Tseng, Shuiwang Ji, Jieping Ye
This paper describes an approach to allow end users to define new procedures through tutorial instruction. Our approach allows users to specify procedures in natural language in t...