DeepLearn 2022 Spring
5th International School
on Deep Learning
Guimarães, Portugal · April 18-22, 2022
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deeplearn-speakers-smith-miles

Kate Smith-Miles

University of Melbourne

Stress-testing Algorithms via Instance Space Analysis

Summary

Instance Space Analysis (ISA) is a recently developed methodology to support objective testing of algorithms. Rather than reporting algorithm performance on average across a chosen set of test problems, as is standard practice, ISA offers a more nuanced understanding of the unique strengths and weaknesses of algorithms across different regions of the instance space that may otherwise be hidden on average. It also facilitates objective assessment of any bias in the chosen test instances, and provides guidance about the adequacy of benchmark test suites. This talk provides an overview of the ISA methodology, and the online software tools that are enabling its worldwide adoption in many disciplines. A case study comparing algorithms for university timetabling is presented to illustrate the methodology and tools.

Short bio

Kate Smith-Miles is a Melbourne Laureate Professor of Applied Mathematics in the School of Mathematics and Statistics at The University of Melbourne, and Director of a doctoral training centre for Optimisation Technologies, Integrated Methodologies and Applications (OPTIMA, see optima.org.au). Kate obtained a B.Sc(Hons) in Mathematics and a Ph.D. in Electrical Engineering, both from The University of Melbourne. She has published 2 books on neural networks and data mining, and over 280 refereed journal and international conference papers in the areas of neural networks, optimisation, data mining, and various applied mathematics topics. She has supervised 29 PhD students to completion, and has been awarded over AUD$20 million in competitive grants, including a prestigious Australian Laureate Fellowship from the Australian Research Council, which enabled her Instance Space Analysis methodology to be advanced and expanded into an online tool (matilda.unimelb.edu.au). Her awards include the Australian Mathematical Society Medal in 2010 for distinguished research; the EO Tuck Medal from ANZIAM in 2017 for outstanding research and distinguished service; and the Ren Potts Medal for outstanding research in the theory and practice of operations research from the Australian Society for Operations Research in 2019.

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deeplearn-speakers-karamLina J. Karam
Kyle KeaneKyle Keane
deeplearn-speakers-xiaoming-liuXiaoming Liu
Jennifer NgadiubaJennifer Ngadiuba
Lucila Ohno-MachadoLucila Ohno-Machado
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deeplearn-speakers-royKaushik Roy
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Yvan SaeysYvan Saeys
deeplearn-speakers-schultzMartin Schultz
Mihai SurdeanuMihai Surdeanu
deeplearn-speakers-vallecorsaSofia Vallecorsa
deeplearn-speakers-vazirgiannisMichalis Vazirgiannis
Guowei WeiGuowei Wei
deeplearn-speakers-xiaowei-xuXiaowei Xu
deeplearn-speakers-zhaoGuoying Zhao
Zhongming ZhaoZhongming Zhao

DeepLearn 2022 Spring

CO-ORGANIZERS

Algoritmi Center, University of Minho, Guimarães

School of Engineering, University of Minho

Intelligent Systems Associate Laboratory, University of Minho

Rovira i Virgili University

Municipality of Guimarães

Institute for Research Development, Training and Advice – IRDTA, Brussels/London

Active links
  • DeepLearn 2022 Autumn – 7th International School on Deep Learning
  • DeepLearn 2022 Summer – 6th International School on Deep Learning
  • TPNC 2020 & 2021 – 9th-10th International Conference on the Theory and Practice of Natural Computing
  • SLSP 2020 & 2021 – 8th-9th International Conference on Statistical Language and Speech Processing
  • AlCoB 2020 & 2021 – 7th-8th International Conference on Algorithms for Computational Biology
  • LATA 2020 & 2021 – 14th-15th International Conference on Language and Automata Theory and Applications
Past links
  • DeepLearn 2021 Summer
  • DeepLearn 2019
  • DeepLearn 2018
  • DeepLearn 2017
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