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Sumio Watanabe
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Cited by
Year
Asymptotic equivalence of Bayes cross validation and widely applicable information criterion in singular learning theory.
S Watanabe
Journal of machine learning research 11 (12), 3571-3594, 2010
28632010
A widely applicable Bayesian information criterion
S Watanabe
Journal of Machine Learning Research 14, 867-897, 2013
9372013
Algebraic geometry and statistical learning theory
S Watanabe
Cambridge university press, 2009
4552009
Algebraic analysis for nonidentifiable learning machines
S Watanabe
Neural Computation 13 (4), 899-933, 2001
2952001
Singularities in mixture models and upper bounds of stochastic complexity
K Yamazaki, S Watanabe
Neural networks 16 (7), 1029-1038, 2003
1432003
Algebraic geometrical methods for hierarchical learning machines
S Watanabe
Neural Networks 14 (8), 1049-1060, 2001
1232001
An ultrasonic visual sensor for three-dimensional object recognition using neural networks
S Watanabe, M Yoneyama
IEEE transactions on Robotics and Automation 8 (2), 240-249, 1992
1171992
Stochastic complexities of reduced rank regression in Bayesian estimation
M Aoyagi, S Watanabe
Neural Networks 18 (7), 924-933, 2005
1122005
Equations of states in singular statistical estimation
S Watanabe
Neural Networks 23 (1), 20-34, 2010
1022010
Mathematical theory of Bayesian statistics
S Watanabe
Chapman and Hall/CRC, 2018
982018
A network of chaotic elements for information processing
S Ishi, K Fukumizu, S Watanabe
Neural Networks 9 (1), 25-40, 1996
981996
Stochastic complexities of Gaussian mixtures in variational Bayesian approximation
K Watanabe, S Watanabe
The Journal of Machine Learning Research 7, 625-644, 2006
652006
Asymptotic behavior of exchange ratio in exchange Monte Carlo method
K Nagata, S Watanabe
Neural Networks 21 (7), 980-988, 2008
632008
Algebraic analysis for singular statistical estimation
S Watanabe
Algorithmic Learning Theory: 10th International Conference, ALTf99 Tokyo c, 1999
601999
Almost all learning machines are singular
S Watanabe
2007 IEEE Symposium on Foundations of Computational Intelligence, 383-388, 2007
552007
Neural network learning system inferring an input-output relationship from a set of given input and output samples
S Watanabe, K Fukumizu
US Patent 5,479,576, 1995
551995
Ultrasonic robot eyes using neural networks
S Watanabe, M Yoneyama
IEEE transactions on ultrasonics, ferroelectrics, and frequency control 37 c, 1990
531990
Three-dimensional object imaging method and system
S Watanabe
US Patent 5,031,154, 1991
471991
Plural neural network system having a successive approximation learning method
S Watanabe
US Patent 5,095,443, 1992
461992
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MARUZEN eBook Library, 2012
442012
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