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JMLR
2008
94views more  JMLR 2008»
13 years 5 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 5 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
13 years 7 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
13 years 7 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
13 years 12 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