Publications (Contd.)

Refereed Conference Papers

Kazunori Iwata. Reducing the Computational Cost of Shape Matching with the Distance Set, Proceedings of the 23rd International Conference on Pattern Recognition, (in Cancun, Mexico), pp. 1506-1511, Dec. 2016. [Data Set]

Kazunori Iwata, Nobuo Suematsu, and Akira Hayashi. A New Shape Descriptor Based on an Angular-Linear Probability Distribution, Proceedings of the 3rd IAPR Asian Conference on Pattern Recognition, (in Kuala Lumpur, Malaysia), pp. 484-488, Nov. 2015. [Data Set]

Kosei Kurisu, Nobuo Suematsu, Kazunori Iwata, and Akira Hayashi. Segmentation Using a Spatially Correlated Mixture Model with Gaussian Process Priors, Proceedings of the 2nd IAPR Asian Conference on Pattern Recognition, (in Okinawa, Japan), pp. 59-63, Nov. 2013.

Akira Hayashi, Kazunori Iwata, and Nobuo Suematsu. Finding the Most Likely Upper Level State Sequence for Hierarchical HMMs, Proceedings of the 1st International Conference on Statistical Language and Speech Processing, (in Tarragona, Spain), Lecture Notes in Computer Science, vol. 7978, pp. 111-122, Jul. 2013.

Kazunori Iwata. Placing Landmarks Suitably for Shape Analysis by Optimization, Proceedings of the 21st International Conference on Pattern Recognition, (in Tsukuba, Japan), pp. 2359-2362, Nov. 2012. [Handout]

Satoshi Kaneko, Akira Hayashi, Nobuo Suematsu and Kazunori Iwata. Hierarchical Hidden Conditional Random Fields for Information Extraction, Proceedings of the 5th International Conference on Learning and Intelligent Optimization, (in Rome, Italy), Lecture Notes in Computer Science, vol. 6683, pp. 191-202, Nov. 2011.

Katsutoshi Ueaoki and Kazunori Iwata. A Novel Shape Descriptor Based on Von Mises Distributions, Proceedings of the 2nd World Congress on Nature and Biologically Inspired Computing, (in Kitakyushu, Japan), pp. 312-317, Dec. 2010.

Kazunori Iwata. An Information-Spectrum Approach to Analysis of Return Maximization in Reinforcement Learning, Proceedings of the 17th International Conference on Neural Information Processing, (in Sydney, Australia), Lecture Notes in Computer Science, vol. 6443, pp. 478-485, Nov. 2010.

Kenji Ono, Kazunori Iwata and Akira Hayashi. An Action-Selection Strategy Insensitive to Parameter-Settings in Reinforcement Learning, Proceedings of ICROS-SICE International Joint Conference 2009, (in Fukuoka, Japan), pp. 1012-1017, Aug. 2009.

Kazunori Iwata and Akira Hayashi. Sampling Curve Images to Find Similarities among Parts of Images, Proceedings of the 15th International Conference on Neural Information Processing, (in Auckland, New Zealand), Lecture Notes in Computer Science, vol. 5506, pp. 663-670, July 2009.

Kazunori Iwata. An Information-Theoretic Class of Stochastic Decision Processes, Proceedings of the 2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, (in Sydney, Australia), pp. 340-344, Dec. 2008.

Kazushi Ikeda and Kazunori Iwata. Information Geometry and Information Theory in Machine Learning, Proceedings of the 14th International Conference on Neural Information Processing, (in Kitakyushu, Japan), Lecture Notes in Computer Science, vol. 4985, pp. 295-304, June 2008.

Kazunori Iwata and Akira Hayashi. Identifying the Underlying Hierarchical Structure of Clusters in Cluster Analysis, Proceedings of the 17th International Conference on Artificial Neural Networks, (in Porto, Portugal), Lecture Notes in Computer Science, vol. 4669, pp. 311-320, Sep. 2007.

Kazunori Iwata and Akira Hayashi. Theory of a Probabilistic-Dependence Measure of Dissimilarity among Multiple Clusters, Proceedings of the 16th International Conference on Artificial Neural Networks, (in Athens, Greece), Lecture Notes in Computer Science, vol. 4132, pp. 311-320, Sep. 2006.

Kazunori Iwata, Hideaki Sakai and Kazushi Ikeda. Stochastic Processes for Return Maximization in Reinforcement Learning, Proceedings of the 15th International Conference on Artificial Neural Networks, (in Warsaw, Poland), Lecture Notes in Computer Science, vol. 3697, pp. 209-214, Sep. 2005.

Kazunori Iwata, Hideaki Sakai and Kazushi Ikeda. Return Maximization in General Decision Processes of Reinforcement Learning, Proceedings of the International Symposium on the Art of Statistical Metaware, (in Tokyo, Japan), pp. 314-315, ISM Report on Research and Education No. 21, Mar. 2005.

Kazushi Ikeda, Takao Komoto and Kazunori Iwata. Asymptotic Properties of the New Support Vector Machines, Proceedings of the International Symposium on the Art of Statistical Metaware, (in Tokyo, Japan), pp. 310-311, ISM Report on Research and Education No. 21, Mar. 2005.

Kazunori Iwata, Kazushi Ikeda and Hideaki Sakai. Stochastic Complexity of Reinforcement Learning, Proceedings of the Brain Inspired Cognitive Systems, (in Stirling, Scotland, UK), NC1-3, University of Stirling, Aug. 2004.

Kazunori Iwata, Kazushi Ikeda and Hideaki Sakai. Asymptotic Equipartition Property on Empirical Sequence in Reinforcement Learning, Proceedings of the 2nd IASTED International Conference on Neural Networks and Computational Intelligence, (in Grindelwald, Switzerland), pp. 90-95, ACTA Press, Feb. 2004.

Kazunori Iwata and Kazushi Ikeda. Temporal Difference Coding in Reinforcement Learning, Proceedings of the 4th International Conference on Intelligent Data Engineering and Automated Learning, (in Hong Kong, China), Lecture Notes in Computer Science, vol. 2690, pp. 218-227, Springer-Verlag, Mar. 2003.

Kazunori Iwata and Naohiro Ishii. Discrepancy as a Quality Measure for Avoiding Classification Bias, Proceedings of the 2002 IEEE International Symposium on Intelligent Control, (in Vancouver, Canada), pp. 532-537, Omnipress, Oct. 2002.

Kazunori Iwata and Naohiro Ishii. Lempel-Ziv Coding in Reinforcement Learning, Proceedings of the 3rd International Conference on Intelligent Data Engineering and Automated Learning, (in Manchester, UK), Lecture Notes in Computer Science, vol. 2412, pp. 531-537, Springer-Verlag, Aug. 2002.

Kazunori Iwata and Naohiro Ishii. A Strategy for Creating Initial Data on Active Learning of Multi-layer Perceptron, Intelligent Agent Technology : Research and Development, Proceedings of the 2nd Asia-Pacific Conference on Intelligent Agent Technology, (in Maebashi, Japan), World Scientific, pp. 180-189, Oct. 2001.

Kazunori Iwata, Koichiro Yamauchi, and Naohiro Ishii. Complexity-based Method for Exploration-Exploitation Dilemma in Reinforcement Learning, Proceedings of the 2nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, (in Nagoya, Japan), pp. 63-70, Aug. 2001.

Kazunori Iwata, Nobuhiro Ito, Koichiro Yamauchi, and Naohiro Ishii. Combining Exploitation-based and Exploration-based Approach in Reinforcement Learning, Proceedings of the 2nd International Conference on Intelligent Data Engineering and Automated Learning, (in Hong Kong, China), Lecture Notes in Computer Science, vol. 1983, Springer-Verlag, pp. 326-331, Dec. 2000.

Kazunori Iwata, Nobuhiro Ito, Koichiro Yamauchi, and Naohiro Ishii. Exploitation/Exploration Learning for MDP Environment, Proceedings of the 2000 IEEE International Conference on Industrial Electronics, Control and Instrumentation, (in Nagoya, Japan), pp. 149-154, Oct. 2000.




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