Neural Information Processing

The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitutes the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. The 296 full papers presented were carefully reviewed and selected from 431 submissions. The 4 volumes are organized in topical sections on deep and reinforcement learning; big data analysis; neural data analysis; robotics and control; bio-inspired/energy efficient information processing; whole brain architecture; neurodynamics; bioinformatics; biomedical engineering; data mining and cybersecurity workshop; machine learning; neuromorphic hardware; sensory perception; pattern recognition; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological and graph based clustering methods; computational intelligence; data mining; deep neural networks; computational and cognitive neurosciences; theory and algorithms.

• embedded systems
• genetic algorithms
• neural networks
• pattern recognition
• swarm intelligence
• big data
• biometric authentication
• brain-computer interface
• cellular neural network
• cloud computing
• computational intelligence
• data mining
• evolutionary algorithm
• image semantics
• natural language processing
• particle swarm optimization
• recommender system
• self-organizing maps

• The University of Tokyo, Tokyo, Japan

  Akira Hirose

• Kobe University, Kobe, Japan

  Seiichi Ozawa

• Okinawa Institute of Science and Technology Graduate University, Onna, Japan

  Kenji Doya

• Nara Institute of Science and Technology, Ikoma, Japan

  Kazushi Ikeda

• Kyungpook National University, Daegu, Korea (Republic of)

  Minho Lee

• Chinese Academy of Sciences, Beijing, China

  Derong Liu

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