Naonori Ueda

Naonori Ueda

NTT Communication Science Laboratories,
Senior Distinguished Scientist /
Machine Learning・Data Science Center, Director

http://www.kecl.ntt.co.jp/as/members/ueda/index.html

Research Area

Statistical Machine Learning, Bayesian Modeling, Data Mining, Pattern Recognition

Biography

Naonori Ueda received the B.S., M.S., and Ph D degrees in Communication Engineering from Osaka University, Osaka, Japan, in 1982, 1984, and 1992, respectively. In 1984, he joined the Electrical Communication Laboratories, NTT, Japan, where he was engaged in research on image processing, pattern recognition, and computer vision. In 1991, he joined the NTT Communication Science Laboratories, where he has invented a significant learning principle for optimal vector quantizer design and has developed some novel learning algorithms including deterministic annealing EM (DAEM) algorithm, ensemble learning, the split and merge EM (SMEM) algorithm, semi-supervised learning, variational Bayesian model search algorithm for mixture models and its application to speech recognition, and probabilistic generative models for multi-labeled text in WWW. His current research interests include parametric and non-parametric Bayesian approach to machine learning, pattern recognition, data mining, signal processing, and cyber-physical systems. From 1993 to 1994, he was a visiting scholar at Purdue University, West Lafayette, USA. Currently, he is a senior distinguished scientist of NTT Communication Science Laboratoris and director of Machine Learning・Data Science Center. He is a member of Information Processing Society of Japan (IPSJ), the Institute of Electronics, Information, and Communication Engineers (IEICE), and IEEE.

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