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» Introduction to Causal Inference
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87
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ICML
2010
IEEE
14 years 10 months ago
Learning Temporal Causal Graphs for Relational Time-Series Analysis
Learning temporal causal graph structures from multivariate time-series data reveals important dependency relationships between current observations and histories, and provides a ...
Yan Liu 0002, Alexandru Niculescu-Mizil, Aurelie C...
89
Voted
CORR
2012
Springer
163views Education» more  CORR 2012»
13 years 5 months ago
The Structure of Signals: Causal Interdependence Models for Games of Incomplete Information
Traditional economic models typically treat private information, or signals, as generated from some underlying state. Recent work has explicated alternative models, where signals ...
Michael P. Wellman, Lu Hong, Scott E. Page
AAAI
2011
13 years 9 months ago
Transportability of Causal and Statistical Relations: A Formal Approach
We address the problem of transferring information learned from experiments to a different environment, in which only passive observations can be collected. We introduce a formal ...
Judea Pearl, Elias Bareinboim
ICCV
2005
IEEE
15 years 3 months ago
KALMANSAC: Robust Filtering by Consensus
We propose an algorithm to perform causal inference of the state of a dynamical model when the measurements are corrupted by outliers. While the optimal (maximumlikelihood) soluti...
Andrea Vedaldi, Hailin Jin, Paolo Favaro, Stefano ...
ICSE
2010
IEEE-ACM
15 years 2 months ago
An eclectic approach for change impact analysis
Change impact analysis aims at identifying software artifacts being affected by a change. In the past, this problem has been addressed by approaches relying on static, dynamic, a...
Michele Ceccarelli, Luigi Cerulo, Gerardo Canfora,...