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CIMCA
2005
IEEE
16 years 9 days ago
Statistical Learning Procedure in Loopy Belief Propagation for Probabilistic Image Processing
We give a fast and practical algorithm for statistical learning hyperparameters from observable data in probabilistic image processing, which is based on Gaussian graphical model ...
Kazuyuki Tanaka
ICA
2004
Springer
16 years 2 days ago
Postnonlinear Overcomplete Blind Source Separation Using Sparse Sources
Abstract. We present an approach for blindly decomposing an observed random vector x into f(As) where f is a diagonal function i.e. f = f1 × . . . × fm with one-dimensional funct...
Fabian J. Theis, Shun-ichi Amari
ATAL
2010
Springer
15 years 7 months ago
Closing the learning-planning loop with predictive state representations
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon
ECCC
2002
86views more  ECCC 2002»
15 years 6 months ago
Classical Physics and the Church-Turing Thesis
Would physical laws permit the construction of computing machines that are capable of solving some problems much faster than the standard computational model? Recent evidence sugge...
Andrew Chi-Chih Yao
BC
1999
78views more  BC 1999»
15 years 6 months ago
The dynamics of goal-directed rhythmical aiming
Based on the kinematics of goal-directed aiming movements in a reciprocal Fitts' task, a minimal limit cycle model is proposed that is capable of producing the behavior observ...
Denis Mottet, Reinoud J. Bootsma