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05/18/2022
Probability trees and the value of a single intervention
The most fundamental problem in statistical causality is determining cau...
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05/17/2022
Moral reinforcement learning using actual causation
Reinforcement learning systems will to a greater and greater extent make...
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05/17/2022
Active learning of causal probability trees
The past two decades have seen a growing interest in combining causal in...
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10/29/2020
Causal variables from reinforcement learning using generalized Bellman equations
Many open problems in machine learning are intrinsically related to caus...
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08/12/2015
Bayesian Dropout
Dropout has recently emerged as a powerful and simple method for trainin...
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11/28/2014
Efficient inference of overlapping communities in complex networks
We discuss two views on extending existing methods for complex network m...
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05/31/2014
Adaptive Reconfiguration Moves for Dirichlet Mixtures
Bayesian mixture models are widely applied for unsupervised learning and...
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11/11/2013