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Big data are encountered in various areas, including Internet search, social networks, finance, business sectors, meteorology, genomics, complex physics simulations, biological and environmental research. Machine learning as an important tool of big data analytics is playing more and more important roles in the big data era. However, the characteristics of large volume, high velocity, variety and veracity bring challenges to current machine learning techniques. It is therefore desirable to discuss (1) how to scale up existing machine learning techniques for modeling and analyzing big data from various domains; (2) how to design new machine learning algorithms for various parallel/distributed machine learning platforms (such as Hadoop, GraphLab, Spark, etc.); and (3) how to design universal machine learning interfaces for GPUs or cloud computing architectures, and so on.

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Topics of Interest Distributed data analytics architectures Data separation and integration techniques Machine learning algorithms for GPUs Machine learning algorithms for clouds Machine learning algorithms for clusters Theory and algorithms of data reduction techniques for big data Online/incremental/stochastic learning algorithms Random projection Hashing techniques Data sampling algorithms Theory and algorithms of large-scale matrix approximation Bound analysis of matrix approximation algorithms Distributed matrix factorization Distributed multiway array analysis Online dictionary learning Distributed topic modeling algorithms Heterogeneous learning on big multimodal data Multiview learning Multitask learning Transfer learning Semi-supervised learning Active learning Temporal analysis and spatial analysis in big data Real-time analysis for data stream Trend prediction in financial data Topic detection in instant message systems Real time modeling of events in dynamic networks Spatial modeling on maps Scalable machine learning in large graphs Communities discovery and analysis in social networks Link prediction in networks Anomaly detection in social networks Fusion of information from multiple blogs, rating systems, and social networks Integration of text, videos, images, sounds in social networks Recommender systems Novel applications of scalable machine learning in big data Decision making with big data Counterfactual reasoning with big data Medical/health informatics big data analysis Security big data analysis Astronomy big data analysis Biological big data analysis Urban/smart city big data analysis Education big data analysis
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重要日期
  • 10月27日

    2014

    会议日期

  • 10月27日 2014

    注册截止日期

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IEEE Computer Society
International Society of Granular Computing
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