INNS-BigData 2015 - Inaugural INNS Big Data conference 2015

The aim of INNS-BigData’2015 conference is to promote new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms), implementations on different computing platforms (e.g. neuromorphic, GPUs, clouds, clusters) and applications of Big Data Analytics to solve real-world problems (e.g. weather prediction, transportation, energy management).
Topics and Areas include, but not limited to:
Autonomous, online, incremental learning ? theory, algorithms and applications in big data
High dimensional data, feature selection, feature transformation ? theory, algorithms and applications for big data
Scalable algorithms for big data
Learning algorithms for high-velocity streaming data
Kernel methods and statistical learning theory
Big data streams analytics
Deep neural network learning
Machine vision and big data
Brain-machine interfaces and big data
Cognitive modeling and big data
Embodied robotics and big data
Fuzzy systems and big data
Evolutionary systems and big data
Evolving systems for big data analytics
Neuromorphic hardware for scalable machine learning
Parallel and distributed computing for big data analytics (cloud, map-reduce, etc.)
Big data and collective intelligence/collaborative learning
Big data and hybrid systems
Big data and self-aware systems
Big Data and infrastructure
Big data analytics and healthcare/medical applications
Big data analytics and energy systems/smart grids
Big data analytics and transportation systems
Big data analytics in large sensor networks
Big data and machine learning in computational biology, bioinformatics
Recommendation systems/collaborative filtering for big data
Big data visualization
Online multimedia/ stream/ text analytics
Link and graph mining
Big data and cloud computing, large scale stream processing on the cloud
Paper Submission and Publication
Original works submitted as a regular paper limited to a maximum of 8 pages using the Procedia Computer Science Standard template (available here) will be published in the proceedings. It will be peer-reviewed by at least three Program Committee members on the basis of technical quality, relevance, originality, significance and clarity. At least one author of an accepted submission to the conference should register with a regular fee to present their work at the conference.
Accepted papers will be published in the conference proceedings by Elsevier.