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» Feature selection based on the training set manipulation
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JAIR
2010
131views more  JAIR 2010»
15 years 5 months ago
Automatic Induction of Bellman-Error Features for Probabilistic Planning
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
Jia-Hong Wu, Robert Givan
ML
2000
ACM
15 years 6 months ago
Maximizing Theory Accuracy Through Selective Reinterpretation
Existing methods for exploiting awed domain theories depend on the use of a su ciently large set of training examples for diagnosing and repairing aws in the theory. In this paper,...
Shlomo Argamon-Engelson, Moshe Koppel, Hillel Walt...
IUI
2012
ACM
14 years 2 months ago
1F: one accessory feature design for gesture recognizers
One Feature (1F) is a simple and intuitive pruning strategy that reduces considerably the amount of computations required by Nearest-Neighbor gesture classifiers while still pres...
Radu-Daniel Vatavu
3DOR
2010
15 years 1 months ago
Learning the Compositional Structure of Man-Made Objects for 3D Shape Retrieval
While approaches based on local features play a more and more important role for 3D shape retrieval, the problems of feature selection and similarity measurement between sets of l...
Raoul Wessel, Reinhard Klein
222
Voted
ICCV
2011
IEEE
14 years 6 months ago
Feature Seeding for Action Recognition
Progress in action recognition has been in large part due to advances in the features that drive learning-based methods. However, the relative sparsity of training data and the ri...
Pyry Matikainen, Rahul Sukthankar, Martial Hebert