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» Learning Gaussian processes from multiple tasks
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ECML
2006
Springer
15 years 7 months ago
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Sébastien Jodogne, Cyril Briquet, Justus H....
CIS
2005
Springer
15 years 8 months ago
Two Adaptive Matching Learning Algorithms for Independent Component Analysis
Independent component analysis (ICA) has been applied in many fields of signal processing and many ICA learning algorithms have been proposed from different perspectives. However...
Jinwen Ma, Fei Ge, Dengpan Gao
ML
2000
ACM
157views Machine Learning» more  ML 2000»
15 years 3 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins
AVSS
2009
IEEE
15 years 10 months ago
Global Illumination Compensation for Background Subtraction Using Gaussian-Based Background Difference Modeling
This paper presents a background segmentation technique, which is able to process acceptable segmentation masks under fast global illumination changes. The histogram of the frame-...
Julien A. Vijverberg, Marijn J. H. Loomans, Cornel...
CORR
2011
Springer
219views Education» more  CORR 2011»
14 years 10 months ago
Active Markov Information-Theoretic Path Planning for Robotic Environmental Sensing
Recent research in multi-robot exploration and mapping has focused on sampling environmental fields, which are typically modeled using the Gaussian process (GP). Existing informa...
Kian Hsiang Low, John M. Dolan, Pradeep K. Khosla