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211
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AAAI
2010
15 years 8 months ago
2010
Multi-label learning deals with data associated with multiple labels simultaneously. Previous work on multi-label learning assumes that for each instance, the "full" lab...
138
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AAAI
2010
15 years 8 months ago
2010
The results of the latest International Probabilistic Planning Competition (IPPC-2008) indicate that the presence of dead ends, states with no trajectory to the goal, makes MDPs h...
172
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AAAI
2010
15 years 8 months ago
2010
The AI community has achieved great success in designing high-performance algorithms for hard combinatorial problems, given both considerable domain knowledge and considerable eff...
180
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AAAI
2010
15 years 8 months ago
2010
Partially-observable Markov decision processes (POMDPs) provide a powerful model for sequential decision-making problems with partially-observed state and are known to have (appro...
176
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AAAI
2010
15 years 8 months ago
2010
Relational Markov Decision Processes (MDP) are a useraction for stochastic planning problems since one can develop abstract solutions for them that are independent of domain size ...