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SODA
2010
ACM
190views Algorithms» more  SODA 2010»
14 years 5 months ago
One-Counter Markov Decision Processes
We study the computational complexity of some central analysis problems for One-Counter Markov Decision Processes (OC-MDPs), a class of finitely-presented, countable-state MDPs. O...
Tomas Brazdil, Vaclav Brozek, Kousha Etessami, Ant...
AAAI
2007
13 years 10 months ago
On the Partial Observability of Temporal Uncertainty
We explore a means to both model and reason about partial observability within the scope of constraintbased temporal reasoning. Prior studies of uncertainty in Temporal CSPs have ...
Michael D. Moffitt
TEC
2002
128views more  TEC 2002»
13 years 7 months ago
A framework for evolutionary optimization with approximate fitness functions
It is not unusual that an approximate model is needed for fitness evaluation in evolutionary computation. In this case, the convergence properties of the evolutionary algorithm are...
Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
PODS
2008
ACM
141views Database» more  PODS 2008»
14 years 7 months ago
On the complexity of deriving schema mappings from database instances
We introduce a theoretical framework for discovering relationships between two database instances over distinct and unknown schemata. This framework is grounded in the context of ...
Pierre Senellart, Georg Gottlob
IJCNN
2008
IEEE
14 years 2 months ago
Active Meta-Learning with Uncertainty Sampling and Outlier Detection
Abstract— Meta-Learning has been used to predict the performance of learning algorithms based on descriptive features of the learning problems. Each training example in this cont...
Ricardo Bastos Cavalcante Prudêncio, Teresa ...