In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
In the origin detection problem an algorithm is given a set S of documents, ordered by creation time, and a query document D. It needs to output for every consecutive sequence of ...
Ossama Abdel Hamid, Behshad Behzadi, Stefan Christ...
Local aspects of Web search -- associating Web content and queries with geography -- is a topic of growing interest. However, the underlying question of how spatial variation is m...
Lars Backstrom, Jon M. Kleinberg, Ravi Kumar, Jasm...