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Ihaka Lecture Series: Interactive visualisation and fast computation of the solution path for convex clustering and biclustering

  • Ihaka Lecture Series 2017 MATH event
  • Date: Wednesday 22 March 2017, 06:30PM to 22 March 2017, 07:30PM
  • Location: Room DA02, Dovedale Village, Dovedale Campus
  • Presented By: Dr Genevera Allen, Departments of Statistics & Electrical & Computer Engineering, Rice University
  • Ticket: Free

Clustering is a fundamental tool for exploratory analysis of big data that finds groups of similar observations. Recently, several have suggested convex approaches to clustering and biclustering, which simultaneously groups features and observations. These methods fit cluster means and use a convex fusion penalty to encourage the means to fuse together to yield a group of fused observations, or a cluster.

A major advantage of convex clustering is that one tuning parameter determines both the number of clusters and the cluster assignments. As this tuning parameter is increased, observations begin to fuse together yielding a continuous and nested family of clusters that we term the convex clustering solution path. In this talk, I will present new fast algorithms to approximately compute the convex clustering solution path and new visualisation tools to dynamically and interactively explore the clustering solutions. I will demonstrate these R+shiny tools on examples from text mining and cancer genomics.

Genevera Allen is the Dobelman Family Junior Chair and an Assistant Professor of Statistics and Electrical and Computer Engineering at Rice University. 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 in 2010 under the mentorship of Professor Robert Tibshirani, and her bachelors, also in statistics, from Rice University in 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. The recipient of several honours including a National Science Foundation CAREER award and the International Biometric Society's Young Statistician Showcase award, she also represented the American Statistical Association (ASA) at the Coalition for National Science Funding on Capitol Hill in 2013 and 2014, 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. She is also the recipient of research grant awards from the Ken Kennedy Institute for Information Technology, the National Science Foundation (NSF), and joint initiatives between NSF and the National Institutes of Health. 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 traveling, Texas craft beers, and playing viola.

This event is part of the Ihaka Lecture Series and is live streamed from University of Auckland’s Department of Statistics.

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Richard Penny

richard.penny@canterbury.ac.nz

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