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» The Structure of First-Order Causality
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ICCV
2005
IEEE
14 years 1 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 ...
ICDM
2009
IEEE
152views Data Mining» more  ICDM 2009»
13 years 5 months ago
A Sparsification Approach for Temporal Graphical Model Decomposition
Temporal causal modeling can be used to recover the causal structure among a group of relevant time series variables. Several methods have been developed to explicitly construct te...
Ning Ruan, Ruoming Jin, Victor E. Lee, Kun Huang
AIME
2009
Springer
14 years 2 months ago
Analysing Clinical Guidelines' Contents with Deontic and Rhetorical Structures
The computerisation of clinical guidelines can greatly benefit from the automatic analysis of their content using Natural Language Processing techniques. Because of the central rol...
Gersende Georg, Hugo Hernault, Marc Cavazza, Helmu...
AIPS
2008
13 years 10 months ago
Structural Patterns Heuristics via Fork Decomposition
We consider a generalization of the PDB homomorphism abstractions to what is called "structural patterns". The bais in abstracting the problem in hand into provably trac...
Michael Katz, Carmel Domshlak
UAI
1998
13 years 9 months ago
Learning the Structure of Dynamic Probabilistic Networks
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
Nir Friedman, Kevin P. Murphy, Stuart J. Russell