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- An invitation to the mathematics of machine learning
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- Home
- Our school
- Study with us
- Our research
-
Student life & resources
Postgraduate research
- Info for new students
- Current research students
- Postgraduate conference
- Postgraduate events
- Postgraduate student awards
- Michael Tallis PhD Research Travel Award
- Information about research theses
- Past research students
- Resources
- Entry requirements
- PhD projects
- Obtaining funding
- Application & fee information
Student services
- Help for postgraduate students
- Thesis guidelines
- School assessment policies
- Computing information
- Mathematics Drop-in Centre
- Consultation
- Statistics Consultation Service
- Academic advice
- Enrolment variation
- Changing tutorials
- Illness or misadventure
- Application form for existing casual tutors
- ARC grants Head of School sign off
- Computing facilities
- Choosing your major
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Abstract:
Machine learning is a field of research that proposes and analyses algorithms for induction-i.e., generalising from examples---and applies them to applications such as search engines, bioinformatics, weather and stock forecasting, automated translation, and image recognition. In recent years, research in this area has increasingly made use of wide range of ideas from mathematics, particularly statistics, differential geometry, information, graph and probability theory, as well as functional and convex analysis.
In this talk I will give a broad overview of machine learning and some of the mathematics I've encountered in my own research. My aim is to impart some of my excitement for what is a topical, engaging, challenging and varied area of research for people with a solid background in mathematics.