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JAIR
2010
131views more  JAIR 2010»
13 years 3 months ago
Automatic Induction of Bellman-Error Features for Probabilistic Planning
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
Jia-Hong Wu, Robert Givan
AIPS
2007
13 years 7 months ago
Discovering Relational Domain Features for Probabilistic Planning
In sequential decision-making problems formulated as Markov decision processes, state-value function approximation using domain features is a critical technique for scaling up the...
Jia-Hong Wu, Robert Givan
SIGIR
2003
ACM
13 years 10 months ago
Text categorization by boosting automatically extracted concepts
Term-based representations of documents have found widespread use in information retrieval. However, one of the main shortcomings of such methods is that they largely disregard le...
Lijuan Cai, Thomas Hofmann
JAIR
2006
157views more  JAIR 2006»
13 years 4 months ago
Decision-Theoretic Planning with non-Markovian Rewards
A decision process in which rewards depend on history rather than merely on the current state is called a decision process with non-Markovian rewards (NMRDP). In decisiontheoretic...
Sylvie Thiébaux, Charles Gretton, John K. S...
MICCAI
2001
Springer
13 years 9 months ago
Valmet: A New Validation Tool for Assessing and Improving 3D Object Segmentation
Extracting 3D structures from volumetric images like MRI or CT is becoming a routine process for diagnosis based on quantitation, for radiotherapy planning, for surgical planning a...
Guido Gerig, Matthieu Jomier, Miranda Chakos