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Joseph Fourier Seminars [EPS-UAM]: "Clustering Big Data", Prof. Anil K. Jain

10/06/2013
Joseph Fourier

On June 3 2013 we had the pleasure to welcome Prof. Anil K. Jain of the Michigan State University (USA) and attend his seminar "Clustering Big Data", within "SEMINARIOS JOSEPH FOURIER [EPS-UAM]: Investigación e innovación de gran impacto en las TIC" that is being held in the Escuela Politécnica Superior.

Prof. Anil K. Jain's research interests include pattern recognition, computer vision and biometric recognition. His articles on biometrics have appeared in Scientific American, Nature, IEEE Spectrum, Comm. ACM, IEEE Computer, Proc. IEEE, Encarta, Scholarpedia, and MIT Technology Review..

Clustering is one of the most popular tools for data exploration and data organization that has been widely used in almost every scientific discipline that collects data. Given the exponential growth in data generation (estimated to be over 35 trillion gigabytes by the year 2020), clustering is receiving renewed interest and use in applications such as social networks, image retrieval, web search and gene expression analysis. In this talk

During his seminar, Prof. Anil K. Jain introduced the data clustering problem and discussed the challenges and opportunities in the research on large-scale clustering, with the focus on two main issues: (i) how to define pairwise similarity between objects? and (ii) how to efficiently cluster hundreds of millions of objects?

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