We consider the task of devising large-margin based surrogate losses for the learning to rank problem. In this learning to rank setting, the traditional hinge loss for structured ...
We study sparse principal components analysis in the high-dimensional setting, where p (the number of variables) can be much larger than n (the number of observations). We prove o...
Many real-world problems are inherently hierarchically structured. The use of this structure in an agent’s policy may well be the key to improved scalability and higher performa...
In this paper, we propose a novel formulation of the network clique detection problem by introducing a general network data representation framework. We show connections between o...
Xiaoye Jiang, Yuan Yao, Han Liu, Leonidas J. Guiba...
We show that the stick-breaking construction of the beta process due to Paisley et al. (2010) can be obtained from the characterization of the beta process as a Poisson process. S...
John William Paisley, David M. Blei, Michael I. Jo...