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» Hard Constraints for Grammatical Function Labelling
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ACL
2010
13 years 2 months ago
Hard Constraints for Grammatical Function Labelling
For languages with (semi-) free word order (such as German), labelling grammatical functions on top of phrase-structural constituent analyses is crucial for making them interpreta...
Wolfgang Seeker, Ines Rehbein, Jonas Kuhn, Josef v...
CVPR
2005
IEEE
14 years 6 months ago
Digital Tapestry
This paper addresses the novel problem of automatically synthesizing an output image from a large collection of different input images. The synthesized image, called a digital tap...
Carsten Rother, Sanjiv Kumar, Vladimir Kolmogorov,...
SIGIR
2008
ACM
13 years 4 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
TIP
2010
182views more  TIP 2010»
12 years 11 months ago
Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction
We propose a unified manifold learning framework for semi-supervised and unsupervised dimension reduction by employing a simple but effective linear regression function to map the ...
Feiping Nie, Dong Xu, Ivor Wai-Hung Tsang, Changsh...
DAGM
2009
Springer
13 years 11 months ago
Active Structured Learning for High-Speed Object Detection
High-speed smooth and accurate visual tracking of objects in arbitrary, unstructured environments is essential for robotics and human motion analysis. However, building a system th...
Christoph H. Lampert, Jan Peters