Yoshifusa Ito

According to our database1, Yoshifusa Ito authored at least 26 papers between 1991 and 2014.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

1995
2000
2005
2010
0
1
2
3
1
1
1
1
1
1
1
2
1
1
2
1
1
2
1
1
1
1
2
1
1
1

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2014
Estimation of Hidden Markov Chains by a Neural Network.
Proceedings of the Neural Information Processing - 21st International Conference, 2014

2012
Simultaneous Learning of Several Bayesian and Mahalanobis Discriminant Functions by a Neural Network with Memory Nodes.
Proceedings of the Neural Information Processing - 19th International Conference, 2012

2011
Simultaneous learning of several Bayesian and Mahalanobis discriminant functions by a neural network with additional nodes.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

A New Algorithm for Learning Mahalanobis Discriminant Functions by a Neural Network.
Proceedings of the Neural Information Processing - 18th International Conference, 2011

2010
Simultaneous Learning of Several Bayesian Discriminant Functions by a Neural Network with Additional Nodes.
Aust. J. Intell. Inf. Process. Syst., 2010

2009
Learning of Mahalanobis Discriminant Functions by a Neural Network.
Proceedings of the Neural Information Processing, 16th International Conference, 2009

2008
Simultaneous Approximations of Polynomials and Derivatives and Their Applications to Neural Networks.
Neural Comput., 2008

Multi-category Bayesian Decision by Neural Networks.
Proceedings of the Artificial Neural Networks, 2008

2007
A Neural Network having Fewer Inner Constants to be Trained and Bayesian Decision.
Proceedings of the International Joint Conference on Neural Networks, 2007

Learning of Bayesian Discriminant Functions by a Layered Neural Network.
Proceedings of the Neural Information Processing, 14th International Conference, 2007

2006
Discriminant Analysis by a Neural Network with Mahalanobis Distance.
Proceedings of the Artificial Neural Networks, 2006

2005
Bayesian decision theory on three-layer neural networks.
Neurocomputing, 2005

Bayesian Learning of Neural Networks Adapted to Changes of Prior Probabilities.
Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

2003
Activation Functions Defined on Higher-Dimensional Spaces for Approximation on Compact Sets with and without Scaling.
Neural Comput., 2003

Multicategory Bayesian Decision Using a Three-Layer Neural Network.
Proceedings of the Artificial Neural Networks and Neural Information Processing, 2003

2002
A Weak Condition on Linear Independence of Unscaled Shifts of a Function and Finite Mappings by Neural Networks.
Proceedings of the Artificial Neural Networks, 2002

2001
Approximation of Bayesian Discriminant Function by Neural Networks in Terms of Kullback-Leibler Information.
Proceedings of the Artificial Neural Networks, 2001

Bayesian decision theory on three layered neural networks.
Proceedings of the 9th European Symposium on Artificial Neural Networks, 2001

2000
Surface-Tracing Approximation by Basis Functions and Its Application to Neural Networks.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

1999
Cultures of neurons on micro-electrode array and control of their axon growth in hybrid retinal implant.
Proceedings of the International Joint Conference Neural Networks, 1999

1996
Nonlinearity creates linear independence.
Adv. Comput. Math., 1996

1994
Approximation Capability of Layered Neural Networks with Sigmoid Units on Two Layers.
Neural Comput., 1994

1993
Extension of approximation capability of three layered neural networks to derivatives.
Proceedings of International Conference on Neural Networks (ICNN'88), San Francisco, CA, USA, March 28, 1993

1992
Approximation of continuous functions on R<sup>d</sup> by linear combinations of shifted rotations of a sigmoid function with and without scaling.
Neural Networks, 1992

1991
Approximation of functions on a compact set by finite sums of a sigmoid function without scaling.
Neural Networks, 1991

Representation of functions by superpositions of a step or sigmoid function and their applications to neural network theory.
Neural Networks, 1991


  Loading...