Faculty Database - NAKADA Yohei

Books and Papers

Conference Presentations

Academic Qualifications

Career History

Major Subjects

Research Topics, Consignment Studies & KAKENHI Researches

（Last updated : 2022-09-04 12:09:23）

NAKADA Yohei
Department Undergraduate School , School of Interdisciplinary Mathematical Sciences

Position Associate Professor

■ Books and Papers

1.	2018/10	Article	"3D visualization tool for player and ball tracking data in basketball" pp.372-381 (Collaboration)
2.	2018/07	Article	"Effects Selection Tool with Visual Saliency Map" pp.109-112 (Collaboration)
3.	2016/11	Article	``Improving on deterministic approximate Bayesian inferences for mixture distributions'' IEEE Transactions on Neural Networks and Learning Systems 27(16),pp.2282-2300 (Single)
4.	2016/03	Article	``Predicting viewer-perceived activity/dominance in soccer games with stick-breaking HMM using data from a fixed set of cameras'' Multimedia tools and Applications 75(6),pp.3081-3119 (Collaboration)
5.	2014/01	Article	``Online Bayesian learning with natural sequential prior distribution'' IEEE Trans Neural Netw Learn Syst. 25(1),pp.40-54 (Collaboration)
6.	2013/04	Article	``Scene detection using a large number of text features'' ITE Transactions on Media Technology and Applications 1(2),pp.157-166 (Collaboration)
7.	2013/02	Article	``Expectation-maximization algorithms for inference in Dirichlet processes mixture'' Pattern Analysis & Applications 16(1),pp.55-67 (Collaboration)
8.	2012/02	Article	``Bayesian event detection for sport games with hidden Markov model'' Pattern Analysis & Applications 15(1),pp.59-72 (Collaboration)
9.	2008/10	Book	``A hierarchical Bayesian hidden Markov model for multi-dimensional discrete data'' Frontiers in Robotics pp.357-374 (Collaboration)
10.	2005/01	Article	``Bayesian reconstructions and predictions of nonlinear dynamical systems via the hybrid Monte Carlo scheme" Signal Processing 85(1),pp.129-145 (Collaboration)
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■ Conference Presentations

1.	2019/12/06	Quantification of pass plays based on geometric features of formations in team sports (The 10th International Symposium on Information and Communication Technology)
2.	2018/12/01	Effect-selection tool using visual saliency maps and its evaluations (Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems in conjunction with Intelligent Systems Workshop 2018)
3.	2018/12/01	Improvement of visualization method for attack patterns in team sports (Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems in conjunction with Intelligent Systems Workshop 2018)
4.	2018/08/31	Effects selection tool for improving visual attraction of a target object (IEEE 20th International Workshop on Multimedia Signal Processing)
5.	2017/11/28	Effects selection technique for improving visual attraction via vsual saliency map (2017 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2017))
6.	2012/06/23	A control variate method using a Metropolis transition kernel with zero variance (Bayesian Inference and Stochastic Computation 2012 workshop)
7.	2011/12/19	An improved deterministic implementation method for Bayesian mixture distributions (10th International Conference on Machine Learning and Applications and Workshops (ICMLA))
8.	2011/07/18	Infinite mixture model approach for protein function prediction algorithm utilizing hidden Markov model and Bayesian network model with Dirichlet process prior (19th Annual International Conference on Intelligent Systems for Molecular Biology and 10th European Conference on Computational Biology)
9.	2010/09/28	An MCMC algorithm for gene regulatory network prediction with Bayesian network (2010 International Conference on Bioinfomatics(InCoB2010))
10.	2010/07/12	A gene regulatory network prediction algorithm using a Gaussian Bayesian network model with a Box-Cox transformation (2010 Annual international conference on Intelligent Systems for Molecular Biology (ISMB2010))
11.	2010/07/12	A non-parametric Bayesian algorithm for predicting gene regulatory networks with a Gaussian process (2010 Annual international conference on Intelligent Systems for Molecular Biology (ISMB2010))
12.	2010/07/11	A novel gene ontology prediction algorithm using infinite mixtures of hidden Markov and binary models with a Dirichlet process prior (2010 Annual international conference on Intelligent Systems for Molecular Biology (ISMB2010))
13.	2009/06/23	Dirichlet process EM algorithm for semi-supervised Learning (7th Workshop on Bayesian Nonparametrics)
14.	2009/06/23	Maximum A Posteriori estimation for Dirichlet process language models (7th Workshop on Bayesian Nonparametrics)
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■ Academic Qualifications

1.	2004/09～2007/09	〔Doctorial Course〕, Waseda University, Accomplished credits for doctoral program
2.	2009/02 Degree Acquisition	Waseda University,
3.	1999/04～2001/03	〔Master Course〕, Waseda University, Completed,
4.	1995/04～1999/03	Waseda University, Graduated,

■ Career History

1.	2018/04～	Associate Professor
2.	2014/04～2018/03	Lecturer
3.	2011/03～2014/04	Assistant Professor
4.	2010/04～2011/03	Research Assistant
5.	2006/04～2009/03	Research Assistant
6.	2001/04～2004/06	Researcher
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■ Research Topics, Consignment Studies & KAKENHI Researches

2004/09～

Improvement of Bayesian learning methods (Key Word : )