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ICMLA
2009
15 years 4 months ago
Regularizing the Local Similarity Discriminant Analysis Classifier
Abstract--We investigate parameter-based and distributionbased approaches to regularizing the generative, similarity-based classifier called local similarity discriminant analysis ...
Luca Cazzanti, Maya R. Gupta
CVPR
2007
IEEE
16 years 8 months ago
Learning and Matching Line Aspects for Articulated Objects
Traditional aspect graphs are topology-based and are impractical for articulated objects. In this work we learn a small number of aspects, or prototypical views, from video data. ...
Xiaofeng Ren
ECML
2005
Springer
16 years 6 days ago
A Comparison of Approaches for Learning Probability Trees
Probability trees (or Probability Estimation Trees, PET’s) are decision trees with probability distributions in the leaves. Several alternative approaches for learning probabilit...
Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice...
IJCNN
2007
IEEE
16 years 29 days ago
Transfer Learning in Decision Trees
— Most research in machine learning focuses on scenarios in which a learner faces a single learning task, independently of other learning tasks or prior knowledge. In reality, ho...
Jun Won Lee, Christophe G. Giraud-Carrier
ASPDAC
2005
ACM
85views Hardware» more  ASPDAC 2005»
16 years 7 days ago
Integration of supercubing and learning in a SAT solver
Abstract— Learning is an essential pruning technique in modern SAT solvers, but it exploits a relatively small amount of information that can be deduced from the conflicts. Rece...
Domagoj Babic, Alan J. Hu