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» Ensemble Algorithms in Reinforcement Learning
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ICCV
2007
IEEE
16 years 6 months ago
Robust Visual Tracking Based on Incremental Tensor Subspace Learning
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, ...
ICML
2005
IEEE
16 years 5 months ago
Combining model-based and instance-based learning for first order regression
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...
Kurt Driessens, Saso Dzeroski
KDD
2008
ACM
104views Data Mining» more  KDD 2008»
16 years 4 months ago
Learning methods for lung tumor markerless gating in image-guided radiotherapy
In an idealized gated radiotherapy treatment, radiation is delivered only when the tumor is at the right position. For gated lung cancer radiotherapy, it is difficult to generate ...
Ying Cui, Jennifer G. Dy, Gregory C. Sharp, Brian ...
AROBOTS
2008
131views more  AROBOTS 2008»
15 years 3 months ago
Active audition using the parameter-less self-organising map
This paper presents a novel method for enabling a robot to determine the position of a sound source in three dimensions using just two microphones and interaction with its environm...
Erik Berglund, Joaquin Sitte, Gordon Wyeth
CORR
2006
Springer
140views Education» more  CORR 2006»
15 years 4 months ago
Nearly optimal exploration-exploitation decision thresholds
While in general trading off exploration and exploitation in reinforcement learning is hard, under some formulations relatively simple solutions exist. Optimal decision thresholds ...
Christos Dimitrakakis