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SIGIR
2008
ACM
13 years 7 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
ICCV
2003
IEEE
14 years 9 months ago
Machine Learning and Multiscale Methods in the Identification of Bivalve Larvae
This paper describes a novel application of support vector machines and multiscale texture and color invariants to a problem in biological oceanography: the identification of 6 sp...
Sanjay Tiwari, Scott Gallager
ICML
2005
IEEE
14 years 8 months ago
Learning class-discriminative dynamic Bayesian networks
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
John Burge, Terran Lane
ICMLA
2009
13 years 5 months ago
Learning Geographic Regions using Location Based Services in Next Generation Networks
Abstract--In this paper we apply classification to learn geographic regions using Location Based Services (LBS) in Next Generation Networks (NGN). We assume that the information in...
Yuheng He, Attila Bilgic
COLING
2008
13 years 9 months ago
Choosing the Right Translation: A Syntactically Informed Classification Approach
One style of Multi-Engine Machine Translation architecture involves choosing the best of a set of outputs from different systems. Choosing the best translation from an arbitrary s...
Simon Zwarts, Mark Dras