Unsupervised word representations are very useful in NLP tasks both as inputs to learning algorithms and as extra word features in NLP systems. However, most of these models are b...
Eric H. Huang, Richard Socher, Christopher D. Mann...
Unsupervised learning methods often involve summarizing the data using a small number of parameters. In certain domains, only a small subset of the available data is relevant for ...
We propose a new framework to study properties of consistency in a Constraint Network from the perspective of properties of set intersection. Our framework comes with a proof sche...
Appearance-based methods, based on statistical models of the pixel values in an image (region) rather than geometrical object models, are increasingly popular in computer vision. I...
—Previous studies have demonstrated that document clustering performance can be improved significantly in lower dimensional linear subspaces. Recently, matrix factorization base...