Given a model family and a set of unlabeled examples, one could either label specific examples or state general constraints--both provide information about the desired model. In g...
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
We demonstrate the effectiveness of multilingual learning for unsupervised part-of-speech tagging. The key hypothesis of multilingual learning is that by combining cues from multi...
Benjamin Snyder, Tahira Naseem, Jacob Eisenstein, ...
The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...
—We consider the problem of inferring and modeling topics in a sequence of documents with known publication dates. The documents at a given time are each characterized by a topic...
Iulian Pruteanu-Malinici, Lu Ren, John William Pai...