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» A Framework for Multiple-Instance Learning
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NIPS
2008
13 years 10 months ago
Structured ranking learning using cumulative distribution networks
Ranking is at the heart of many information retrieval applications. Unlike standard regression or classification in which we predict outputs independently, in ranking we are inter...
Jim C. Huang, Brendan J. Frey
ICASSP
2011
IEEE
13 years 1 months ago
Adaptive appearance learning for visual object tracking
This paper addresses online learning of reference object distribution in the context of two hybrid tracking schemes that combine the mean shift with local point feature correspond...
Zulfiqar Hassan Khan, Irene Yu-Hua Gu
CVPR
2005
IEEE
14 years 11 months ago
Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data
We address the problem of segmenting 3D scan data into objects or object classes. Our segmentation framework is based on a subclass of Markov Random Fields (MRFs) which support ef...
Dragomir Anguelov, Benjamin Taskar, Vassil Chatalb...
GECCO
2005
Springer
119views Optimization» more  GECCO 2005»
14 years 2 months ago
Learning, anticipation and time-deception in evolutionary online dynamic optimization
In this paper we focus on an important source of problem– difficulty in (online) dynamic optimization problems that has so far received significantly less attention than the tr...
Peter A. N. Bosman
AIIA
1995
Springer
14 years 27 days ago
Learning Programs in Different Paradigms using Genetic Programming
Genetic Programming (GP) is a method of automatically inducing programs by representing them as parse trees. In theory, programs in any computer languages can be translated to par...
Man Leung Wong, Kwong-Sak Leung