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AAAI
1992
14 years 11 months ago
Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning
It is often useful for a robot to construct a spatial representation of its environment from experiments and observations, in other words, to learn a map of its environment by exp...
Thomas Dean, Dana Angluin, Kenneth Basye, Sean P. ...
114
Voted
ISOLA
2010
Springer
14 years 8 months ago
LivingKnowledge: Kernel Methods for Relational Learning and Semantic Modeling
Latest results of statistical learning theory have provided techniques such us pattern analysis and relational learning, which help in modeling system behavior, e.g. the semantics ...
Alessandro Moschitti
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
14 years 7 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
ISBI
2008
IEEE
15 years 10 months ago
A learning based hierarchical model for vessel segmentation
In this paper we present a learning based method for vessel segmentation in angiographic videos. Vessel Segmentation is an important task in medical imaging and has been investiga...
Richard Socher, Adrian Barbu, Dorin Comaniciu
ECAI
2004
Springer
15 years 3 months ago
Combining Multiple Answers for Learning Mathematical Structures from Visual Observation
Learning general truths from the observation of simple domains and, further, learning how to use this knowledge are essential capabilities for any intelligent agent to understand ...
Paulo Santos, Derek R. Magee, Anthony G. Cohn, Dav...