|Thursday 21st January, 10.00 am||Corcoran Memorial Lecture
Title: (Not) Aggregating Data
Abstract: The ability to generate, access and combine multiple sources of data presents both opportunity and challenge for statistical science. An exemplar phenomenon is the charge to collate all relevant data for the purposes of comprehensive control and analysis. However, this ambition is often thwarted by the relentless expansion in volume of data, as well as issues of data provenance, privacy and governance. Alternatives to creating ‘the one database to rule them all’ are emerging. An appealing approach is the concept of federated learning, also known as distributed analysis, which aims to analyse disparate datasets in situ. In this presentation, I will discuss some case studies that have motivated our interest in federated learning, review the statistical and computational issues involved in the development of such an approach, and outline our recent efforts to understand and implement a federated learning model in the context of the Australian Cancer Atlas.
|Kerrie Mengersen, Distinguished Professor in Statistics at the Queensland University of Technology in Brisbane, Australia
|Thursday 18th February, 3.30 pm||Distinguished Speaker Seminar||Bin Yu, Chancellor’s Professor, Departments of Statistics and Electrical Engineering & Computer Science, UC Berkeley|
|Thursday 12th March, 3.30 pm||Florence Nightingale Lecture||Bernard Silverman, Professor of Modern Slavery Statistics, University of Nottingham and Emeritus Professor of Statistics, University of Oxford|
|Thursday 29th April, 3.30 pm||Distinguished Speaker Seminar||Sara van der Geer Professor at the Seminar for Statistics, ETH Zurich|
|Friday 18th June, 3.30 pm||Distinguished Speaker Seminar||Susan Murphy, Professor of statistics and computer science at Harvard John A. Paulson School of Engineering and Applied Sciences|