Kazunori Iwata

Orcid: 0000-0002-2638-7288

Affiliations:
  • Hiroshima City University, Japan
  • Kyoto University, Japan (PhD)


According to our database1, Kazunori Iwata authored at least 17 papers between 2003 and 2020.

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

Timeline

Legend:

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PhD thesis 
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Bibliography

2020
Revisiting a Nearest Neighbor Method for Shape Classification.
IEICE Trans. Inf. Syst., 2020

2019
Sampling Shape Contours Using Optimization over a Geometric Graph.
IEICE Trans. Inf. Syst., 2019

2018
Shape Clustering as a Type of Procrustes Analysis.
Proceedings of the Neural Information Processing - 25th International Conference, 2018

2017
Extending the Peak Bandwidth of Parameters for Softmax Selection in Reinforcement Learning.
IEEE Trans. Neural Networks Learn. Syst., 2017

2015
A Spatially Correlated Mixture Model for Image Segmentation.
IEICE Trans. Inf. Syst., 2015

2013
Marginalized Viterbi algorithm for hierarchical hidden Markov models.
Pattern Recognit., 2013

2011
An information-theoretic analysis of return maximization in reinforcement learning.
Neural Networks, 2011

Matching Handwritten Line Drawings with Von Mises Distributions.
IEICE Trans. Inf. Syst., 2011

2008
A Redundancy-Based Measure of Dissimilarity among Probability Distributions for Hierarchical Clustering Criteria.
IEEE Trans. Pattern Anal. Mach. Intell., 2008

2007
Information Geometry and Information Theory in Machine Learning.
Proceedings of the Neural Information Processing, 14th International Conference, 2007

2006
A statistical property of multiagent learning based on Markov decision process.
IEEE Trans. Neural Networks, 2006

The asymptotic equipartition property in reinforcement learning and its relation to return maximization.
Neural Networks, 2006

2005
On the Effects of Domain Size and Complexity in Empirical Distribution of Reinforcement Learning.
IEICE Trans. Inf. Syst., 2005

Stochastic Processes for Return Maximization in Reinforcement Learning.
Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

2004
A new criterion using information gain for action selection strategy in reinforcement learning.
IEEE Trans. Neural Networks, 2004

Asymptotic equipartition property on empirical sequence in reinforcement learning.
Proceedings of the IASTED International Conference on Neural Networks and Computational Intelligence, 2004

2003
Temporal Difference Coding in Reinforcement Learning.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2003


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