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» The structure of intrinsic complexity of learning
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ICML
2010
IEEE
13 years 8 months ago
Learning Efficiently with Approximate Inference via Dual Losses
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
ECCV
2010
Springer
13 years 11 months ago
Modeling Temporal Structure of Decomposable Motion Segments for Activity Classification
Abstract. Much recent research in human activity recognition has focused on the problem of recognizing simple repetitive (walking, running, waving) and punctual actions (sitting up...
IVC
2008
101views more  IVC 2008»
13 years 7 months ago
Occlusion analysis: Learning and utilising depth maps in object tracking
Complex scenes such as underground stations and malls are composed of static occlusion structures such as walls, entrances, columns, turnstiles and barriers. Unless this occlusion...
Darrel Greenhill, John-Paul Renno, James Orwell, G...
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
14 years 8 months ago
Spectral domain-transfer learning
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, ...
IWINAC
2007
Springer
14 years 1 months ago
EDNA: Estimation of Dependency Networks Algorithm
One of the key points in Estimation of Distribution Algorithms (EDAs) is the learning of the probabilistic graphical model used to guide the search: the richer the model the more ...
José A. Gámez, Juan L. Mateo, Jose M...