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» Using model knowledge for learning inverse dynamics
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PAMI
2012
13 years 6 months ago
UBoost: Boosting with the Universum
—It has been shown that the Universum data, which do not belong to either class of the classification problem of interest, may contain useful prior domain knowledge for training...
Chunhua Shen, Peng Wang, Fumin Shen, Hanzi Wang
AIPS
2007
15 years 6 months ago
Using Adaptive Priority Weighting to Direct Search in Probabilistic Scheduling
Many scheduling problems reside in uncertain and dynamic environments – tasks have a nonzero probability of failure and may need to be rescheduled. In these cases, an optimized ...
Andrew M. Sutton, Adele E. Howe, L. Darrell Whitle...
MLG
2007
Springer
15 years 10 months ago
Abductive Stochastic Logic Programs for Metabolic Network Inhibition Learning
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, Jose Santos
COGSCI
2008
139views more  COGSCI 2008»
15 years 3 months ago
A Computational Model of Early Argument Structure Acquisition
How children go about learning the general regularities that govern language, as well as keeping track of the exceptions to them, remains one of the challenging open questions in ...
Afra Alishahi, Suzanne Stevenson
121
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IROS
2008
IEEE
156views Robotics» more  IROS 2008»
15 years 10 months ago
Bayesian state estimation and behavior selection for autonomous robotic exploration in dynamic environments
— In order to be truly autonomous, robots that operate in natural, populated environments must have the ability to create a model of these unpredictable dynamic environments and ...
Georgios Lidoris, Dirk Wollherr, Martin Buss