Zobrazeno 1 - 10
of 156
pro vyhledávání: '"Korb, Kevin"'
The two most commonly used criteria for assessing causal model discovery with artificial data are edit-distance and Kullback-Leibler divergence, measured from the true model to the learned model. Both of these metrics maximally reward the true model.
Externí odkaz:
http://arxiv.org/abs/2111.06029
Causal discovery automates the learning of causal Bayesian networks from data and has been of active interest from their beginning. With the sourcing of large data sets off the internet, interest in scaling up to very large data sets has grown. One a
Externí odkaz:
http://arxiv.org/abs/2107.08140
Autor:
Nicholson, Ann E., Korb, Kevin B., Nyberg, Erik P., Wybrow, Michael, Zukerman, Ingrid, Mascaro, Steven, Thakur, Shreshth, Alvandi, Abraham Oshni, Riley, Jeff, Pearson, Ross, Morris, Shane, Herrmann, Matthieu, Azad, A. K. M., Bolger, Fergus, Hahn, Ulrike, Lagnado, David
In many complex, real-world situations, problem solving and decision making require effective reasoning about causation and uncertainty. However, human reasoning in these cases is prone to confusion and error. Bayesian networks (BNs) are an artificia
Externí odkaz:
http://arxiv.org/abs/2003.01207
Moral graphs were introduced in the 1980s as an intermediate step when transforming a Bayesian network to a junction tree, on which exact belief propagation can be efficiently done. The moral graph of a Bayesian network can be trivially obtained by c
Externí odkaz:
http://arxiv.org/abs/1903.02201
A family of Markov blankets in a faithful Bayesian network satisfies the symmetry and consistency properties. In this paper, we draw a bijection between families of consistent Markov blankets and moral graphs. We define the new concepts of weak recur
Externí odkaz:
http://arxiv.org/abs/1903.01707
The causal discovery of Bayesian networks is an active and important research area, and it is based upon searching the space of causal models for those which can best explain a pattern of probabilistic dependencies shown in the data. However, some of
Externí odkaz:
http://arxiv.org/abs/1607.06617
The application of evolution in the digital realm, with the goal of creating artificial intelligence and artificial life, has a history as long as that of the digital computer itself. We illustrate the intertwined history of these ideas, starting wit
Externí odkaz:
http://arxiv.org/abs/1512.02100
A major problem for the learning of Bayesian networks (BNs) is the exponential number of parameters needed for conditional probability tables. Recent research reduces this complexity by modeling local structure in the probability tables. We examine t
Externí odkaz:
http://arxiv.org/abs/1301.6727
Poker is ideal for testing automated reasoning under uncertainty. It introduces uncertainty both by physical randomization and by incomplete information about opponents hands.Another source OF uncertainty IS the limited information available TO const
Externí odkaz:
http://arxiv.org/abs/1301.6711