Nobuo Suematsu

According to our database, Nobuo Suematsu authored at least 24 papers between 1997 and 2019.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2019

Sampling Shape Contours Using Optimization over a Geometric Graph.

Kazuya Ose, Kazunori Iwata, Nobuo Suematsu

IEICE Trans. Inf. Syst., 2019

2018

A Shape Matching Method Considering Computational Feasibility.

Hiroki Yamamoto, Kazunori Iwata, Nobuo Suematsu, Kazushi Mimura

Proceedings of the 2018 International Conference on Signal Processing and Machine Learning, 2018

Typical Performance of Sparse Signal Recovery from a Linear Measurement with Large Coherence.

Minori Ihara, Kazunori Iwata, Nobuo Suematsu, Kazushi Mimura

Proceedings of the International Symposium on Information Theory and Its Applications, 2018

2017

A sampling method for processing contours drawn with an uncertain stroke order and number.

Kazuya Ose, Kazunori Iwata, Nobuo Suematsu

Proceedings of the Fifteenth IAPR International Conference on Machine Vision Applications, 2017

Extending the Full Procrustes Distance to Anisotropic Scale in Shape Analysis.

Tsukasa Okamoto, Kazunori Iwata, Nobuo Suematsu

Proceedings of the 4th IAPR Asian Conference on Pattern Recognition, 2017

2015

A Spatially Correlated Mixture Model for Image Segmentation.

Kosei Kurisu, Nobuo Suematsu, Kazunori Iwata, Akira Hayashi

IEICE Trans. Inf. Syst., 2015

A new shape descriptor based on an angular-linear probability distribution.

Kazunori Iwata, Nobuo Suematsu, Akira Hayashi

Proceedings of the 3rd IAPR Asian Conference on Pattern Recognition, 2015

2013

Marginalized Viterbi algorithm for hierarchical hidden Markov models.

Akira Hayashi, Kazunori Iwata, Nobuo Suematsu

Pattern Recognit., 2013

Finding the Most Likely Upper Level State Sequence for Hierarchical HMMs.

Akira Hayashi, Kazunori Iwata, Nobuo Suematsu

Proceedings of the Statistical Language and Speech Processing, 2013

Image Segmentation Using a Spatially Correlated Mixture Model with Gaussian Process Priors.

Kosei Kurisu, Nobuo Suematsu, Kazunori Iwata, Akira Hayashi

Proceedings of the 2nd IAPR Asian Conference on Pattern Recognition, 2013

2012

Time series alignment with Gaussian processes.

Nobuo Suematsu, Akira Hayashi

Proceedings of the 21st International Conference on Pattern Recognition, 2012

2011

Matching Handwritten Line Drawings with Von Mises Distributions.

Katsutoshi Ueaoki, Kazunori Iwata, Nobuo Suematsu, Akira Hayashi

IEICE Trans. Inf. Syst., 2011

Hierarchical Hidden Conditional Random Fields for Information Extraction.

Satoshi Kaneko, Akira Hayashi, Nobuo Suematsu, Kazunori Iwata

Proceedings of the Learning and Intelligent Optimization - 5th International Conference, 2011

2010

A nonparametric Bayesian approach to time series alignment.

Shinji Akimoto, Nobuo Suematsu

Proceedings of the Second World Congress on Nature & Biologically Inspired Computing, 2010

2008

Component Reduction for Gaussian Mixture Models.

Kumiko Maebashi, Nobuo Suematsu, Akira Hayashi

IEICE Trans. Inf. Syst., 2008

2007

Component Reduction for Hierarchical Mixture Model Construction.

Kumiko Maebashi, Nobuo Suematsu, Akira Hayashi

Proceedings of the Neural Information Processing, 14th International Conference, 2007

2006

Embedding of time series data by using dynamic time warping distances.

Yuko Mizuhara, Akira Hayashi, Nobuo Suematsu

Syst. Comput. Jpn., 2006

View Independent Gait Identification Using a Particle Filter.

Mitsuharu Emoto, Akira Hayashi, Nobuo Suematsu, Kazunori Iwata

Proceedings of the Advanced Video and Signal Based Surveillance, 2006

2005

Embedding Time Series Data for Classification.

Akira Hayashi, Yuko Mizuhara, Nobuo Suematsu

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2005

Learning with Segment Boundaries for Hierarchical HMMs.

Naoto Gotou, Akira Hayashi, Nobuo Suematsu

Proceedings of the Pattern Recognition and Data Mining, 2005

2002

A multiagent reinforcement learning algorithm using extended optimal response.

Nobuo Suematsu, Akira Hayashi

Proceedings of the First International Joint Conference on Autonomous Agents & Multiagent Systems, 2002

1998

A Reinforcement Learning Algorithm in Partially Observable Environments Using Short-Term Memory.

Nobuo Suematsu, Akira Hayashi

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Viewing Classifier Systems as Model Free Learning in POMDPs.

Akira Hayashi, Nobuo Suematsu

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

1997

A Bayesian Approach to Model Learning in Non-Markovian Environments.

Nobuo Suematsu, Akira Hayashi, Shigang Li

Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997