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JMLR
2008
94views more  JMLR 2008»
13 years 11 months ago
Using Markov Blankets for Causal Structure Learning
We show how a generic feature selection algorithm returning strongly relevant variables can be turned into a causal structure learning algorithm. We prove this under the Faithfuln...
Jean-Philippe Pellet, André Elisseeff
COGSCI
2010
107views more  COGSCI 2010»
13 years 11 months ago
Inferring Hidden Causal Structure
We used a new method to assess how people can infer unobserved causal structure from patterns of observed events. Participants were taught to draw causal graphs, and then shown a ...
Tamar Kushnir, Alison Gopnik, Chris Lucas, Laura S...
AIPS
2008
14 years 1 months ago
Unifying the Causal Graph and Additive Heuristics
Many current heuristics for domain-independent planning, such as Bonet and Geffner's additive heuristic and Hoffmann and Nebel's FF heuristic, are based on delete relaxa...
Malte Helmert, Hector Geffner
AAAI
2008
14 years 1 months ago
Dormant Independence
The construction of causal graphs from non-experimental data rests on a set of constraints that the graph structure imposes on all probability distributions compatible with the gr...
Ilya Shpitser, Judea Pearl
ICDCS
2009
IEEE
14 years 6 months ago
On Optimal Concurrency Control for Optimistic Replication
Concurrency control is a core component in optimistic replication systems. To detect concurrent updates, the system associates each replicated object with metadata, such as, versi...
Weihan Wang, Cristiana Amza