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ICML
2004
IEEE
16 years 7 months ago
Semi-supervised learning using randomized mincuts
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...
PAMI
2011
15 years 1 months ago
Greedy Learning of Binary Latent Trees
—Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
Stefan Harmeling, Christopher K. I. Williams
IPMI
2005
Springer
16 years 7 months ago
Segmenting and Tracking the Left Ventricle by Learning the Dynamics in Cardiac Images
Having accurate left ventricle (LV) segmentations across a cardiac cycle provides useful quantitative (e.g. ejection fraction) and qualitative information for diagnosis of certain ...
Alan S. Willsky, Godtfred Holmvang, Müjdat &C...
PVLDB
2008
131views more  PVLDB 2008»
15 years 5 months ago
Learning to create data-integrating queries
The number of potentially-related data resources available for querying -- databases, data warehouses, virtual integrated schemas -continues to grow rapidly. Perhaps no area has s...
Partha Pratim Talukdar, Marie Jacob, Muhammad Salm...
ISMDA
2001
Springer
15 years 10 months ago
Learning Bayesian-Network Topologies in Realistic Medical Domains
In recent years, a number of algorithms have been developed for learning the structure of Bayesian networks from data. In this paper we apply some of these algorithms to a realist...
Xiaofeng Wu, Peter J. F. Lucas, Susan Kerr, Roelf ...