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Original Thinking Webinar

Dates:6 October 2021
Times:16:30 - 17:30
What is it:Talk
Organiser:Alliance Manchester Business School
Who is it for:University staff, Adults, Alumni, Current University students, General public
Speaker:Julia Handl
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  • In category "Talk"
  • By Alliance Manchester Business School

We all face and make decisions on an ongoing basis, whether at work or in our private lives. The vast majority of these decisions involve trade-offs between multiple criteria, be it healthiness versus taste in our choice of breakfast cereal, cost versus energy efficiency in our choice of a new household utility, or risk versus expected return in our selection of a financial portfolio. Typically, there is considerable conflict between these criteria and, in the presence of such conflict, a single optimal solution may not exist. Taking a sound decision will then require the exploration of a set of alternative trade-offs, and the incorporation of additional preference information.

The same types of trade-offs exist in machine learning applications, where our models frequently have to strike a compromise between a variety of conflicting criteria. In this presentation, I will discuss the various origins of these criteria in a machine learning context. Using a number of examples from my own research, I will then highlight how multicriterion optimisation can support us in exploring a range of alternative trade-off solutions for machine learning problems, supporting the analyst in identifying their preferred model.

Speaker

Julia Handl

Role: Professor in Data Sciences

Organisation: Alliance MBS

Biography: https://www.research.manchester.ac.uk/portal/julia.handl.html

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