Meetings/Workshops on Information & Knowledge Management, Big Data Computing in the United States (USA)

Society for Industrial and Applied Mathematics (SIAM)

Data mining is the computational process for discovering valuable knowledge from data – the core of modern Data Science. It has enormous applications in numerous fields, including science, engineering, healthcare, business, and medicine. Typical datasets in these fields are large, complex, and often noisy. Extracting knowledge from these datasets requires the use of sophisticated, high-performance, and principled analysis techniques and algorithms. These techniques in turn require implementations on high performance computational infrastructure that are carefully tuned for performance. Powerful visualization technologies along with effective user interfaces are also essential to make data mining tools appealing to researchers, analysts, data scientists and application developers from different disciplines, as well as usable by stakeholders.

This conference is held in cooperation with the American Statistical Association.

Probability and Statistics, Game Theory,    Database Technology and Design, Search Engines and Data Mining

Society for Industrial and Applied Mathematics (SIAM)

Sponsored by the SIAM Activity Group on Data Mining and Analytics.

Simons Institute

This conference is focused on the changing role and nature of the discipline of statistics in the time of a data deluge in many applications, and increasing success of artificial intelligence at performing many data analysis tasks. The conference aims to bring together experts in statistical methodology and theory for complex and big data with researchers focused on a range of applications, from genomics to social networks, and to provide opportunities for new researchers to learn about both emerging methods and applications.

MRSI – Mathematical Sciences Research Institute, Berkeley

This summer school will introduce graduate students to sketching-based approaches to computational linear and multi-linear algebra. Sketching here refers to a set of techniques for compressing a matrix, to one with fewer rows, or columns, or entries, usually via various kinds of random linear maps. We will discuss matrix computations, tensor algebras, and such sketching techniques, together with their applications and analysis.

Courses and Events for Math Students and Early Career Researchers,    Applied Mathematics (in general)

MarketsandMarkets - Conferences

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