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» On learning algorithm selection for classification
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113
Voted
ICRA
2005
IEEE
146views Robotics» more  ICRA 2005»
15 years 6 months ago
Probabilistic Gaze Imitation and Saliency Learning in a Robotic Head
— Imitation is a powerful mechanism for transferring knowledge from an instructor to a na¨ıve observer, one that is deeply contingent on a state of shared attention between the...
Aaron P. Shon, David B. Grimes, Chris Baker, Matth...
99
Voted
ICML
2006
IEEE
16 years 1 months ago
Two-dimensional solution path for support vector regression
Recently, a very appealing approach was proposed to compute the entire solution path for support vector classification (SVC) with very low extra computational cost. This approach ...
Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky
109
Voted
ECML
1987
Springer
15 years 4 months ago
Induction in Noisy Domains
This paper examines the induction of classification rules from examples using real-world data. Real-world data is almost always characterized by two features, which are important ...
Peter Clark, Tim Niblett
91
Voted
IPPS
2007
IEEE
15 years 7 months ago
Adaptive Predictor Integration for System Performance Prediction
The integration of multiple predictors promises higher prediction accuracy than the accuracy that can be obtained with a single predictor. The challenge is how to select the best ...
Jian Zhang, Renato J. O. Figueiredo
122
Voted
ICASSP
2010
IEEE
15 years 28 days ago
Semi-Supervised Fisher Linear Discriminant (SFLD)
Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm i...
Seda Remus, Carlo Tomasi