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» Learning with Mixtures of Trees
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ICAART
2010
INSTICC
14 years 6 months ago
Complexity of Stochastic Branch and Bound Methods for Belief Tree Search in Bayesian Reinforcement Learning
There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most...
Christos Dimitrakakis
ECML
2005
Springer
14 years 2 months ago
Learning (k, l)-Contextual Tree Languages for Information Extraction
This paper introduces a novel method for learning a wrapper for extraction of information from web pages, based upon (k,l)-contextual tree languages. It also introduces a method to...
Stefan Raeymaekers, Maurice Bruynooghe, Jan Van de...
ICASSP
2010
IEEE
13 years 9 months ago
Weakly supervised learning with decision trees applied to fisheries acoustics
This paper addresses the training of classification trees for weakly labelled data. We call ”weakly labelled data”, a training set such as the prior labelling information pro...
Riwal Lefort, Ronan Fablet, Jean-Marc Boucher
ECML
2007
Springer
14 years 3 months ago
Transfer Learning in Reinforcement Learning Problems Through Partial Policy Recycling
In this paper we investigate the relation between transfer learning in reinforcement learning with function approximation and supervised learning with concept drift. We present a n...
Jan Ramon, Kurt Driessens, Tom Croonenborghs
ICML
2007
IEEE
14 years 10 months ago
Multi-task reinforcement learning: a hierarchical Bayesian approach
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...