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162
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PKDD
2010
Springer
164views Data Mining» more  PKDD 2010»
14 years 10 months ago
Efficient Planning in Large POMDPs through Policy Graph Based Factorized Approximations
Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
Joni Pajarinen, Jaakko Peltonen, Ari Hottinen, Mik...
ISNN
2011
Springer
14 years 3 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
IJRR
2008
139views more  IJRR 2008»
15 years 22 days ago
Learning to Control in Operational Space
One of the most general frameworks for phrasing control problems for complex, redundant robots is operational space control. However, while this framework is of essential importan...
Jan Peters, Stefan Schaal
100
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NETWORKS
2010
14 years 11 months ago
A mean-variance model for the minimum cost flow problem with stochastic arc costs
This paper considers a minimum cost flow problem where arc costs are uncertain, and the decision maker wishes to minimize both the expected flow cost and the variance of this co...
Stephen D. Boyles, S. Travis Waller
128
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AIRS
2006
Springer
15 years 4 months ago
A Novel Ant-Based Clustering Approach for Document Clustering
Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant Colony Optimization (ACO) is one such algorithm based on s...
Yulan He, Siu Cheung Hui, Yongxiang Sim