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TSMC
2008
132views more  TSMC 2008»
13 years 7 months ago
Ensemble Algorithms in Reinforcement Learning
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...
Marco A. Wiering, Hado van Hasselt
NLPRS
2001
Springer
14 years 4 days ago
Ensembling based on Feature Space Restructuring with Application to WSD
We propose a new ensembling method of Support Vector Machines (SVMs) based on Feature Space Restructuring. In the proposed method, the weighted majority voting method is applied f...
Hiroya Takamura, Hiroyasu Yamada, Taku Kudo, Kaoru...
ICASSP
2011
IEEE
12 years 11 months ago
Modeling musical attributes to characterize ensemble recordings using rhythmic audio features
In this paper, we present the results of a pre-study on music performance analysis of ensemble music. Our aim is to implement a music classification system for the description of...
Jakob Abesser, Olivier Lartillot, Christian Dittma...
BMCBI
2011
13 years 2 months ago
Phenotype Recognition with Combined Features and Random Subspace Classifier Ensemble
Background: Automated, image based high-content screening is a fundamental tool for discovery in biological science. Modern robotic fluorescence microscopes are able to capture th...
Bailing Zhang, Tuan D. Pham
ICDM
2010
IEEE
168views Data Mining» more  ICDM 2010»
13 years 5 months ago
Anomaly Detection Using an Ensemble of Feature Models
We present a new approach to semi-supervised anomaly detection. Given a set of training examples believed to come from the same distribution or class, the task is to learn a model ...
Keith Noto, Carla E. Brodley, Donna K. Slonim