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» A Bayesian Computational Cognitive Model
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ICONIP
2007
15 years 5 months ago
Natural Conjugate Gradient in Variational Inference
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...
ML
2012
ACM
385views Machine Learning» more  ML 2012»
14 years 21 hour ago
An alternative view of variational Bayes and asymptotic approximations of free energy
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
Kazuho Watanabe
ICCV
2007
IEEE
16 years 6 months ago
Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
ACMDIS
2006
ACM
15 years 10 months ago
How do design and evaluation interrelate in HCI research?
Human-Computer Interaction (HCI) is defined by the Association for Computing Machinery (ACM) Special Interest Group on Computer-Human Interaction (SIGCHI) as “a discipline conce...
Christine E. Wania, Michael E. Atwood, Katherine W...
WAPCV
2007
Springer
15 years 10 months ago
Language Label Learning for Visual Concepts Discovered from Video Sequences
Computational models of grounded language learning have been based on the premise that words and concepts are learned simultaneously. Given the mounting cognitive evidence for conc...
Prithwijit Guha, Amitabha Mukerjee