Temporal Difference Coding in Reinforcement Learning. - Kazunori Iwata 002; Kazushi Ikeda (IDEAL, 2003)

Asymptotic equipartition property on empirical sequence in reinforcement learning. - Kazunori Iwata 002; Kazushi Ikeda; Hideaki Sakai (Neural Networks and Computational Intelligence, 2004)

A new criterion using information gain for action selection strategy in reinforcement learning. - Kazunori Iwata 002; Kazushi Ikeda; Hideaki Sakai (IEEE Trans. Neural Networks, 2004)

Stochastic Processes for Return Maximization in Reinforcement Learning. - Kazunori Iwata 002; Hideaki Sakai; Kazushi Ikeda (ICANN (2), 2005)

On the Effects of Domain Size and Complexity in Empirical Distribution of Reinforcement Learning. - Kazunori Iwata 002; Kazushi Ikeda; Hideaki Sakai (IEICE Trans. Inf. Syst., 2005)

The asymptotic equipartition property in reinforcement learning and its relation to return maximization. - Kazunori Iwata 002; Kazushi Ikeda; Hideaki Sakai (Neural Networks, 2006)

A statistical property of multiagent learning based on Markov decision process. - Kazunori Iwata 002; Kazushi Ikeda; Hideaki Sakai (IEEE Trans. Neural Networks, 2006)

Information Geometry and Information Theory in Machine Learning. - Kazushi Ikeda; Kazunori Iwata 002 (ICONIP (2), 2007)

A Redundancy-Based Measure of Dissimilarity among Probability Distributions for Hierarchical Clustering Criteria. - Kazunori Iwata 002; Akira Hayashi (IEEE Trans. Pattern Anal. Mach. Intell., 2008)

Matching Handwritten Line Drawings with Von Mises Distributions. - Katsutoshi Ueaoki; Kazunori Iwata 002; Nobuo Suematsu; Akira Hayashi (IEICE Trans. Inf. Syst., 2011)

An information-theoretic analysis of return maximization in reinforcement learning. - Kazunori Iwata 002 (Neural Networks, 2011)

Marginalized Viterbi algorithm for hierarchical hidden Markov models. - Akira Hayashi; Kazunori Iwata 002; Nobuo Suematsu (Pattern Recognit., 2013)

A Spatially Correlated Mixture Model for Image Segmentation. - Kosei Kurisu; Nobuo Suematsu; Kazunori Iwata 002; Akira Hayashi (IEICE Trans. Inf. Syst., 2015)

Extending the Peak Bandwidth of Parameters for Softmax Selection in Reinforcement Learning. - Kazunori Iwata 002 (IEEE Trans. Neural Networks Learn. Syst., 2017)

Shape Clustering as a Type of Procrustes Analysis. - Kazunori Iwata 002 (ICONIP (4), 2018)

Sampling Shape Contours Using Optimization over a Geometric Graph. - Kazuya Ose; Kazunori Iwata 002; Nobuo Suematsu (IEICE Trans. Inf. Syst., 2019)

Revisiting a Nearest Neighbor Method for Shape Classification. - Kazunori Iwata 002 (IEICE Trans. Inf. Syst., 2020)

Use of several non-Euclidean metrics to compute distances between every two points in a plane bounded convex set. - Kazunori Iwata 002 (J. Comput. Sci., 2025)

Mixture Density Function Estimation in Shape Clustering. - Kazunori Iwata 002 (IEEE Trans. Artif. Intell., 2025)

Making clustering methods workable for shapes using the ordinary Procrustes sum of squares. - Kazunori Iwata 002; Yuki Nontani; Kazushi Mimura (Pattern Recognit., 2026)