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» Causal inference using the algorithmic Markov condition
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EDM
2010
160views Data Mining» more  EDM 2010»
14 years 11 months ago
Using Neural Imaging and Cognitive Modeling to Infer Mental States while Using an Intelligent Tutoring System
Functional magnetic resonance imaging (fMRI) data were collected while students worked with a tutoring system that taught an algebra isomorph. A cognitive model predicted the distr...
Jon M. Fincham, John R. Anderson, Shawn Betts, Jen...
KDD
2009
ACM
364views Data Mining» more  KDD 2009»
15 years 10 months ago
Causality quantification and its applications: structuring and modeling of multivariate time series
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
Takashi Shibuya, Tatsuya Harada, Yasuo Kuniyoshi
IJACTAICIT
2010
153views more  IJACTAICIT 2010»
14 years 4 months ago
Prediction Using Recurrent Neural Network Based Fuzzy Inference system by the Modified Bees Algorithm
In this paper, a recurrent neural network based fuzzy inference system (RNFIS) for prediction is proposed. A recurrent network is embedded in the RNFIS by adding feedback connecti...
Zahra Khanmirzaei, Mohammad Teshnehlab
ICARIS
2005
Springer
15 years 3 months ago
A Markov Chain Model of the B-Cell Algorithm
An exact Markov chain model of the B-cell algorithm (BCA) is constructed via a novel possible transit method. The model is used to formulate a proof that the BCA is convergent abso...
Edward Clark, Andrew Hone, Jon Timmis
ECCV
2008
Springer
15 years 11 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal