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» On learning algorithm selection for classification
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FLAIRS
1998
15 years 8 months ago
Interactively Training Pixel Classifiers
Manual generation of training examples for supervised learning is an expensive process. One way to reduce this cost is to produce training instances that are highly informative. T...
Justus H. Piater, Edward M. Riseman, Paul E. Utgof...
ISDA
2010
IEEE
15 years 4 months ago
Comparing SVM ensembles for imbalanced datasets
Real life datasets often suffer from the problem of class imbalance, which thwarts supervised learning process. In such data sets examples of positive (minority) class are signific...
Vasudha Bhatnagar, Manju Bhardwaj, Ashish Mahabal
ICML
2003
IEEE
16 years 7 months ago
Margin Distribution and Learning
Recent theoretical results have shown that improved bounds on generalization error of classifiers can be obtained by explicitly taking the observed margin distribution of the trai...
Ashutosh Garg, Dan Roth
ML
1998
ACM
153views Machine Learning» more  ML 1998»
15 years 6 months ago
Bayesian Landmark Learning for Mobile Robot Localization
To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optim...
Sebastian Thrun
MAGS
2010
81views more  MAGS 2010»
15 years 1 months ago
Task allocation learning in a multiagent environment: Application to the RoboCupRescue simulation
Coordinating agents in a complex environment is a hard problem, but it can become even harder when certain characteristics of the tasks, like the required number of agents, are un...
Sébastien Paquet, Brahim Chaib-draa, Patric...