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» Using Markov Blankets for Causal Structure Learning
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157
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PRICAI
2000
Springer
15 years 7 months ago
Generating Hierarchical Structure in Reinforcement Learning from State Variables
This paper presents the CQ algorithm which decomposes and solves a Markov Decision Process (MDP) by automatically generating a hierarchy of smaller MDPs using state variables. The ...
Bernhard Hengst
137
Voted
CORR
2010
Springer
105views Education» more  CORR 2010»
15 years 2 months ago
Optimism in Reinforcement Learning Based on Kullback-Leibler Divergence
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Sarah Filippi, Olivier Cappé, Aurelien Gari...
UAI
2008
15 years 5 months ago
Causal discovery of linear acyclic models with arbitrary distributions
An important task in data analysis is the discovery of causal relationships between observed variables. For continuous-valued data, linear acyclic causal models are commonly used ...
Patrik O. Hoyer, Aapo Hyvärinen, Richard Sche...
141
Voted
ICML
2005
IEEE
16 years 4 months ago
Predicting protein folds with structural repeats using a chain graph model
Protein fold recognition is a key step towards inferring the tertiary structures from amino-acid sequences. Complex folds such as those consisting of interacting structural repeat...
Yan Liu, Eric P. Xing, Jaime G. Carbonell
143
Voted
ICML
2006
IEEE
16 years 4 months ago
Discriminative unsupervised learning of structured predictors
We present a new unsupervised algorithm for training structured predictors that is discriminative, convex, and avoids the use of EM. The idea is to formulate an unsupervised versi...
Linli Xu, Dana F. Wilkinson, Finnegan Southey, Dal...