Neural Information Processing: 23rd International Conference, Iconip 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part Iii (lecture Notes In Computer Science)
by Kenji Doya /
2017 / English / PDF
103.1 MB Download
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.
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.
