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CVPR
2012
IEEE
13 years 6 months ago
Geometry constrained sparse coding for single image super-resolution
The choice of the over-complete dictionary that sparsely represents data is of prime importance for sparse codingbased image super-resolution. Sparse coding is a typical unsupervi...
Xiaoqiang Lu, Haoliang Yuan, Pingkun Yan, Yuan Yua...
ACL
2012
13 years 6 months ago
Improving Word Representations via Global Context and Multiple Word Prototypes
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...
ICTAI
2008
IEEE
15 years 10 months ago
Classifying Spend Descriptions with Off-the-Shelf Learning Components
Analyzing spend transactions is essential to organizations for understanding their global procurement. Central to this analysis is the automated classification of these transacti...
Saikat Mukherjee, Dmitriy Fradkin, Michael Roth
DAGSTUHL
2007
15 years 5 months ago
Learning Probabilistic Relational Dynamics for Multiple Tasks
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
Ashwin Deshpande, Brian Milch, Luke S. Zettlemoyer...
COLING
2002
15 years 4 months ago
Learning Question Classifiers
In order to respond correctly to a free form factual question given a large collection of texts, one needs to understand the question to a level that allows determining some of th...
Xin Li, Dan Roth