From January to June 2015, the Canadian Statistical Sciences Institute organized a thematic program on Statistical Inference, Learning and Models in Big Data.
Jun 30, 2016 · This paper gives an overview of the topics covered, describing challenges and strategies that seem common to many different areas of application.
Sep 9, 2015 · This paper gives an overview of the topics covered, describing challenges and strategies that seem common to many different areas of application.
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An overview of the topics covered is given, describing challenges and strategies that seem common to many different areas of application and including some ...
Sep 11, 2015 · Big data provides big opportunities for statistical inference, but perhaps even bigger challenges, often related to differences in volume, ...
This thematic program emphasizes both applied and theoretical aspects of statistical inference, learning and models in big data.
The need for new methods to deal with big data is a common theme in most scientific fields, although its definition tends to vary with the context.
I present several research vignettes on topics at the computation/statistics interface, including the problem of trading off inference and privacy, the problem ...
"Statistical Inference, Learning and Models in Big Data," International Statistical Review, International Statistical Institute, vol. 84(3), pages 371-389 ...
This talk is about supervised learning: building models from data that predict an outcome using a collection of input features. • There are some powerful and ...
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