Nobuo Suematsu

24 papers A* 1A 1B 2C 1Misc 1Journal 6Unranked 12
YearRankTypeTitle / Venue / Authors
2019 J jnl
Sampling Shape Contours Using Optimization over a Geometric Graph.
IEICE Trans. Inf. Syst.
Kazuya Ose, Kazunori Iwata, Nobuo Suematsu
2018 — conf
A Shape Matching Method Considering Computational Feasibility.
SPML
Hiroki Yamamoto, Kazunori Iwata, Nobuo Suematsu, Kazushi Mimura
2018 C conf
Typical Performance of Sparse Signal Recovery from a Linear Measurement with Large Coherence.
ISITA
Minori Ihara, Kazunori Iwata, Nobuo Suematsu, Kazushi Mimura
2017 Misc conf
A sampling method for processing contours drawn with an uncertain stroke order and number.
MVA
Kazuya Ose, Kazunori Iwata, Nobuo Suematsu
2017 — conf
Extending the Full Procrustes Distance to Anisotropic Scale in Shape Analysis.
ACPR
Tsukasa Okamoto, Kazunori Iwata, Nobuo Suematsu
2015 J jnl
A Spatially Correlated Mixture Model for Image Segmentation.
IEICE Trans. Inf. Syst.
Kosei Kurisu, Nobuo Suematsu, Kazunori Iwata, Akira Hayashi
2015 — conf
A new shape descriptor based on an angular-linear probability distribution.
ACPR
Kazunori Iwata, Nobuo Suematsu, Akira Hayashi
2013 — conf
Finding the Most Likely Upper Level State Sequence for Hierarchical HMMs.
SLSP
Akira Hayashi, Kazunori Iwata, Nobuo Suematsu
2013 — conf
Image Segmentation Using a Spatially Correlated Mixture Model with Gaussian Process Priors.
ACPR
Kosei Kurisu, Nobuo Suematsu, Kazunori Iwata, Akira Hayashi
2013 J jnl
Marginalized Viterbi algorithm for hierarchical hidden Markov models.
Pattern Recognit.
Akira Hayashi, Kazunori Iwata, Nobuo Suematsu
2012 B conf
Time series alignment with Gaussian processes.
ICPR
Nobuo Suematsu, Akira Hayashi
2011 — conf
Hierarchical Hidden Conditional Random Fields for Information Extraction.
LION
Satoshi Kaneko, Akira Hayashi, Nobuo Suematsu, Kazunori Iwata
2011 J jnl
Matching Handwritten Line Drawings with Von Mises Distributions.
IEICE Trans. Inf. Syst.
Katsutoshi Ueaoki, Kazunori Iwata, Nobuo Suematsu, Akira Hayashi
2010 — conf
A nonparametric Bayesian approach to time series alignment.
NaBIC
Shinji Akimoto, Nobuo Suematsu
2008 J jnl
Component Reduction for Gaussian Mixture Models.
IEICE Trans. Inf. Syst.
Kumiko Maebashi, Nobuo Suematsu, Akira Hayashi
2007 — conf
Component Reduction for Hierarchical Mixture Model Construction.
ICONIP (2)
Kumiko Maebashi, Nobuo Suematsu, Akira Hayashi
2006 J jnl
Embedding of time series data by using dynamic time warping distances.
Syst. Comput. Jpn.
Yuko Mizuhara, Akira Hayashi, Nobuo Suematsu
2006 B conf
View Independent Gait Identification Using a Particle Filter.
AVSS
Mitsuharu Emoto, Akira Hayashi, Nobuo Suematsu, Kazunori Iwata
2005 — conf
Embedding Time Series Data for Classification.
MLDM
Akira Hayashi, Yuko Mizuhara, Nobuo Suematsu
2005 — conf
Learning with Segment Boundaries for Hierarchical HMMs.
ICAPR (1)
Naoto Gotou, Akira Hayashi, Nobuo Suematsu
2002 A conf
A multiagent reinforcement learning algorithm using extended optimal response.
AAMAS
Nobuo Suematsu, Akira Hayashi
1998 — conf
A Reinforcement Learning Algorithm in Partially Observable Environments Using Short-Term Memory.
NIPS
Nobuo Suematsu, Akira Hayashi
1998 — conf
Viewing Classifier Systems as Model Free Learning in POMDPs.
NIPS
Akira Hayashi, Nobuo Suematsu
1997 A* conf
A Bayesian Approach to Model Learning in Non-Markovian Environments.
ICML
Nobuo Suematsu, Akira Hayashi, Shigang Li