IEEE BigData 2015

Publication Date: 2014-09-29 11:54:06

INNS Conference on Big Data
08-10 August 2015, San Francisco - USA

BIG DATA is not just about storage of and access to data. Analytics play a big role in making sense of that data and exploiting its value. But learning from big data has become a significant challenge and requires development of new types of algorithms. Most machine learning algorithms can’t easily scale up to big data. Plus there are challenges of high-dimensionality, velocity and variety.

The neural network field has historically focused on algorithms that learn in an online, incremental mode without requiring in-memory access to huge amounts of data. This type of learning is not only ideal for streaming data (as in the Industrial Internet or the Internet of Things), but could also be used on stored big data. Neural network technologies thus can become significant components of big data analytics platforms and this inaugural INNS Conference on Big Data will begin that collaborative adventure with big data and other learning technologies.

Thus the aim of this 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).

Paper Submission and Publication
Original works submitted as a regular paper limited to a maximum of 8 pages in IEEE 2-column format 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 the Elsevier.

Important Dates