[ESIP-all] [AGU 2016 FM Session] Call for Abstract: Achieving Deep Learning by Systemizing Machine Learning with Big Data Engines
Kuo, Kwo-Sen (GSFC-612.0)[UNIV OF MARYLAND]
kwo-sen.kuo at nasa.gov
Mon Jun 27 15:29:43 EDT 2016
Please consider submitting an abstract to the following session. Please note the abstract submission deadline of Wednesday, 3 August 2016.
Session ID: 13320
Session Title: Achieving Deep Learning by Systemizing Machine Learning with Big Data Engines
Submit an Abstract to this Session<https://agu.confex.com/agu/fm16/in/papers/index.cgi?sessionid=13320>
Big Data has created a mature class of disruptive technologies that have been adopted by a number of large-scale geoscience data infrastructures. While developments in Big Data are proceeding at pace, advanced machine-automated methods are being introduced to extract information and knowledge from large volumes and varieties of data. However, it is reported that data preparation still takes the majority of the time spent on data mining and/or machine learning exercises. When scalability is realized for both volume and variety, Big Data systems are apt to make such exercise more effortless. They thus serve as ideal platforms to systemize machine learning and to achieve deep learning with much better value. In this session we seek presentations demonstrating the vision of Big Data for geosciences, reports of current machine/deep learning efforts, the challenges such efforts faced and/or are facing, and potentials and solutions in Big Data to address these challenges.
Mike M Little
Jens F Klump
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