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ATAL
2010
Springer
15 years 8 months ago
Closing the learning-planning loop with predictive state representations
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon
MMS
2006
15 years 6 months ago
Collaborative image retrieval via regularized metric learning
In content-based image retrieval (CBIR), relevant images are identified based on their similarities to query images. Most CBIR algorithms are hindered by the semantic gap between ...
Luo Si, Rong Jin, Steven C. H. Hoi, Michael R. Lyu
ICML
2008
IEEE
16 years 7 months ago
A decoupled approach to exemplar-based unsupervised learning
A recent trend in exemplar based unsupervised learning is to formulate the learning problem as a convex optimization problem. Convexity is achieved by restricting the set of possi...
Gökhan H. Bakir, Sebastian Nowozin
CDC
2010
IEEE
118views Control Systems» more  CDC 2010»
15 years 1 months ago
On optimal cooperative patrolling
This work considers the problem of designing optimal multi-agent trajectories to patrol an environment. As performance criterion for optimal patrolling we consider the worst-case t...
Fabio Pasqualetti, Antonio Franchi, Francesco Bull...
JCST
2008
119views more  JCST 2008»
15 years 6 months ago
Mining Frequent Generalized Itemsets and Generalized Association Rules Without Redundancy
This paper presents some new algorithms to efficiently mine max frequent generalized itemsets (g-itemsets) and essential generalized association rules (g-rules). These are compact ...
Daniel Kunkle, Donghui Zhang, Gene Cooperman