The Distinguished Women in Mathematics Lecture Series. Our series of talks by outstanding female mathematicians continues this Friday with an expository talk by Professor Kate Smith-Miles. The talk will be followed by afternoon tea. All are welcome, and the talk is designed to be accessible to students. Date/time: Friday, 27th of September, 3 PM Venue: New Law LT 024 Speaker: Professor Kate Smith-Miles, School of Mathematical Sciences, Monash University Title: Footprints in Instance Space: steps towards a free lunch Abstract: The No-Free-Lunch Theorem tells us that, without prior knowledge of the properties of an instance of a problem, we cannot expect any single algorithm to outperform all others across all instances. If an algorithm performs exceptionally well on a certain class of instances, there will always be some other class of instances where it is outperformed by another algorithm. Understanding how the properties of an instance affect algorithm performance is the key to being able to articulate the strengths and weaknesses of an algorithm, and to anticipate when it is likely to be better than others. In this talk I will present a new methodology for achieving this goal, and demonstrate its applicability to optimization, although it generalizes to other problem domains. The methodology involves: visualizing the set of all possible instances based on features that correlate with difficulty; statistical generalization of algorithm performance in this instance space, shown as a footprint where an algorithm’s performance is deemed to be good; and then measuring the relative area of the footprint of different algorithms. The methodology is applied to provide insights into optimization algorithm performance on the Travelling Salesman Problem and graph colouring. Bio: Kate Smith-Miles is a Professor and Head of the School of Mathematical Sciences at Monash University. Prior to commencing this role in January 2009, she held a Chair in Engineering at Deakin University (where she was Head of the School of Engineering and Information Technology from 2006-2008) and a Chair in Information Technology at Monash University, where she worked from 1996-2006. Kate obtained a B.Sc(Hons) in Mathematics and a Ph.D. in Electrical Engineering, both from the University of Melbourne, Australia. She has published 2 books on neural networks and data mining applications, and over 200 refereed journal and international conference papers in the areas of neural networks, combinatorial optimization, intelligent systems and data mining. She has supervised to completion 20 PhD students, and has been awarded over AUD$10 million in competitive grants, including 10 Australian Research Council grants and industry awards. From 2007-2008 she was Chair of the IEEE Technical Committee on Data Mining (IEEE Computational Intelligence Society). She was elected Fellow of the Institute of Engineers Australia (FIEAust) in 2006, and Fellow of the Australian Mathematical Society (FAustMS) in 2008. She was awarded the Australian Mathematical Society Medal in 2010 for distinguished research. In addition to her academic activities, she also regularly acts as a consultant to industry in the areas of optimisation, data mining, and intelligent systems.