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» Evaluating learning algorithms and classifiers
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86
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ML
2000
ACM
126views Machine Learning» more  ML 2000»
15 years 11 days ago
Learning to Play Chess Using Temporal Differences
In this paper we present TDLEAF( ), a variation on the TD( ) algorithm that enables it to be used in conjunction with game-tree search. We present some experiments in which our che...
Jonathan Baxter, Andrew Tridgell, Lex Weaver
ARTMED
1999
92views more  ARTMED 1999»
15 years 8 days ago
Two-Stage Machine Learning model for guideline development
We present a Two-Stage Machine Learning (ML) model as a data mining method to develop practice guidelines and apply it to the problem of dementia staging. Dementia staging in clin...
Subramani Mani, William Rodman Shankle, Malcolm B....
JAIR
2010
111views more  JAIR 2010»
14 years 11 months ago
Training a Multilingual Sportscaster: Using Perceptual Context to Learn Language
We present a novel framework for learning to interpret and generate language using only perceptual context as supervision. We demonstrate its capabilities by developing a system t...
David L. Chen, Joohyun Kim, Raymond J. Mooney
123
Voted
ICIAR
2009
Springer
14 years 10 months ago
3D Human Pose Estimation from Static Images Using Local Features and Discriminative Learning
In this paper an approach to recover the 3D human body pose from static images is proposed. We adopt a discriminative learning technique to directly infer the 3D pose from appearan...
Suman Sedai, Farid Flitti, Mohammed Bennamoun, Du ...
106
Voted
CVPR
2005
IEEE
16 years 2 months ago
Local Discriminant Embedding and Its Variants
We present a new approach, called local discriminant embedding (LDE), to manifold learning and pattern classification. In our framework, the neighbor and class relations of data a...
Hwann-Tzong Chen, Huang-Wei Chang, Tyng-Luh Liu