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» Learning to learn with the informative vector machine
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ML
2008
ACM
248views Machine Learning» more  ML 2008»
15 years 6 months ago
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
ICML
2005
IEEE
16 years 7 months ago
Bayesian sparse sampling for on-line reward optimization
We present an efficient "sparse sampling" technique for approximating Bayes optimal decision making in reinforcement learning, addressing the well known exploration vers...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...
ML
2006
ACM
187views Machine Learning» more  ML 2006»
15 years 6 months ago
Modeling, analyzing, and synthesizing expressive piano performance with graphical models
Abstract Trained musicians intuitively produce expressive variations that add to their audience's enjoyment. However, there is little quantitative information about the kinds ...
Graham Grindlay, David P. Helmbold
ECML
2004
Springer
16 years 6 days ago
Improving Random Forests
Random forests are one of the most successful ensemble methods which exhibits performance on the level of boosting and support vector machines. The method is fast, robust to noise,...
Marko Robnik-Sikonja
ECTEL
2007
Springer
16 years 1 months ago
Relevance Ranking Metrics for Learning Objects
— The main objetive of this paper is to improve the current status of learning object search. First, the current situation is analyzed and a theretical solution, based on relevan...
Xavier Ochoa, Erik Duval