Thematic Program on Statistical Inference, Learning, and Models for Big Data
January 5 - June 14, 2015
Program Outline
This thematic program emphasized both applied and theoretical aspects of statistical inference, learning and models in big data. The opening conference served as an introduction to the program, concentrating on overview lectures and background preparation. Workshops throughout the semester emphasized deep learning, statistical learning, visualization, networks, health and social policy, and physical sciences. A number of allied activities at PIMS, CRM and AARMS were also planned during the semester. This thematic program is took place in cooperation with the new Canadian Statistical Sciences Institute (CANSSI).
Workshops and Conferences
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Opening Conference and Boot Camp on Big Data
January 12 - 23, 2015
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Workshop on Big Data and Statistical Machine Learning
January 26 - 30, 2015
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Workshop on Optimization and Matrix Methods in Big Data
February 9 - 11, 2015
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Workshop on Visualization for Big Data: Strategies and Principles
February 23 - 27, 2015
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Workshop on Big Data in Health Policy
March 23 - 27, 2015
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Workshop on Big Data for Social Policy
April 13 - 16, 2015
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Closing Conference of the Statistical Inference, Learning, and Models for Big Data Program
June 12 - 13, 2015
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Statistical Inference, Learning and Models in Data Science
September 24 - 27, 2018
Special and Public Lectures
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Coxeter Lecture Series: Michael Jordan
April 7 - 9, 2015
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2015-2016 Distinguished Lecture Series in Statistical Sciences: Terry Speed
April 9 - 10, 2015
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2014-2015 Distinguished Lecture Series in Statistical Sciences: Bin Yu
April 23 - 24, 2015
Courses
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Graduate Course on Large Scale Machine Learning
January 5 - March 23, 2015
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Graduate Course on Topics in Inference for Big Data
January 9 - March 27, 2015
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Short Course on Latent Tree graphical models
April 27 - 29, 2015