Sydney Workshop: Introduction to Unsupervised Learning

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The Statistical Society of Australia and the School of Mathematics and Statistics, University of Sydney are pleased to offer the following workshop:

Introduction to Unsupervised Learning

Presented by

Associate Professor Genevera Allen, Rice University.


About the Course
This short course will present a number of unsupervised statistical machine learning techniques for finding patterns and associations in Big Data. These include dimension reduction techniques such as principal components analysis and non-negative matrix factorization, clustering analysis, and network analysis with graphical models.  The main emphasis will be on practical issues including how to use unsupervised learning techniques to visualize and explore Big Data.  All techniques will be demonstrated through real data examples in R.

This course assumes some previous exposure to probability, statistics, and linear regression, as well as some familiarity with R or another programming language.

Recommended Reading: James et al. (2013) Introduction to Statistical Learning. Springer Series in Statistics. Available for free download at


About the presenter
Genevera Allen is an Associate Professor of Statistics, Computer Science, and Electrical and Computer Engineering at Rice University, Texas. She is also a member of the Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital and Baylor College of Medicine where she holds a joint appointment. Dr Allen received her PhD in statistics from Stanford University (2010), under the mentorship of Prof. Robert Tibshirani, and her bachelors, also in statistics, from Rice University (2006).

Dr Allen’s research focuses on developing statistical methods to help scientists make sense of their ‘Big Data’ in applications such as high-throughput genomics and neuroimaging. Her work lies in the areas of modern multivariate analysis, graphical models, statistical machine learning, and data integration or data fusion. She is the recipient of several honors including a National Science Foundation CAREER award, the International Biometric Society’s Young Statistician Showcase award, and the George R. Brown School of Engineering’s Research and Teaching Excellence Award at Rice University. In 2013 and 2014, she represented the American Statistical Association (ASA) at the Coalition for National Science Funding on Capitol Hill and has had her research highlighted on the House floor in a speech by Congressman McNerney (D-CA). In 2014, Dr Allen was named to the “Forbes ’30 under 30′: Science and Healthcare” list. Dr Allen currently serves as an Associated Editor for Biometrics, the Secretary / Treasurer for the ASA Section on Statistical Computing, and the Program Chair for the ASA Section on Statistical Learning and Data Science.

Outside of work, Dr Allen is a patron of the Houston Symphony and Houston Grand Opera and is involved with several arts organisations throughout Houston. She also enjoys travelling, Texas craft beers, and playing viola.


Workshop Fees
Early Bird Fees (Payment on or before 1 September 2017)

SSA Full Member: $260.00

Non Members: $350.00

SSA Student Members*: $140.00

Non Member Students**: $160.00


Regular Fees (Payment from 1 – 21 September 2017)

SSA Full Member: $350.00

Non Members: $400.00

SSA Student Members*: $200.00

Non Member Students**: $220.00


SSA Student Membership is available for $20 p/a

**Please email proof of full-time student status to [email protected]
Registrations after 21 September 2017 will incur a $100 late fee.

The workshop registration fee includes morning and afternoon tea. You can BYO lunch or purchase lunch at one of the nearby eateries.


Please note 

Workshop participants need to bring their own laptops with the following software installed:

R and Rstudio. R packages ISLR and NMF should be installed. Optional R packages: PMA, cvxbiclustr, XMRF, igraph, huge.

This software can be downloaded here:

For R packages, open Rstudio and enter the command install.packages(“ISLR”) in the R shell. Repeat for other R packages replacing “ISLR” with the corresponding package.


Travel Expenses
Occasionally workshops have to be cancelled due to a lack of subscription. Early registration by as many participants as possible ensures that this will not happen. Please contact the SSA Office before making any travel arrangements to confirm that the workshop will go ahead, because the Society will not be held responsible for any travel or accommodation expenses incurred due to a workshop cancellation.

Cancellation Policy
Cancellations received prior to Thursday, 21 September 2017will be refunded, minus a $50 administration fee. From 21 September 2017 no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to [email protected].




Sydney Workshop: Introduction to Unsupervised Learning
When: 29/09/2017
Time: 8:30 am - 5:00 pm
Cost: from $140 (students)
Location: The University of Sydney,
The University of Sydney,
NSW 2006

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