04711nam 22008055 450 99646537400331620230329175255.03-319-46672-010.1007/978-3-319-46672-9(CKB)3710000000872957(DE-He213)978-3-319-46672-9(MiAaPQ)EBC6296600(MiAaPQ)EBC5591853(Au-PeEL)EBL5591853(OCoLC)960195054(PPN)195511328(EXLCZ)99371000000087295720160929d2016 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierNeural Information Processing[electronic resource] 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part II /edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu1st ed. 2016.Cham :Springer International Publishing :Imprint: Springer,2016.1 online resource (XIX, 739 p. 252 illus.) Theoretical Computer Science and General Issues,2512-2029 ;99483-319-46671-2 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.The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitues 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. .Theoretical Computer Science and General Issues,2512-2029 ;9948Pattern recognition systemsComputer visionArtificial intelligenceComputer scienceData miningApplication softwareAutomated Pattern RecognitionComputer VisionArtificial IntelligenceTheory of ComputationData Mining and Knowledge DiscoveryComputer and Information Systems ApplicationsPattern recognition systems.Computer vision.Artificial intelligence.Computer science.Data mining.Application software.Automated Pattern Recognition.Computer Vision.Artificial Intelligence.Theory of Computation.Data Mining and Knowledge Discovery.Computer and Information Systems Applications.006.4Hirose Akiraedthttp://id.loc.gov/vocabulary/relators/edtOzawa Seiichiedthttp://id.loc.gov/vocabulary/relators/edtDoya Kenjiedthttp://id.loc.gov/vocabulary/relators/edtIkeda Kazushiedthttp://id.loc.gov/vocabulary/relators/edtLee Minhoedthttp://id.loc.gov/vocabulary/relators/edtLiu Derongedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK996465374003316Neural Information Processing2554499UNISA