Amos Storkey (University of Edinburgh) |
Wed 02 Nov 2016, 16:00 - 17:00 |
JCMB 5327 |
If you have a question about this talk, please contact: Kostas Zygalakis (kzygalak)
When tackling common forms of real world problems, we quickly meet a number of constraints that make machine learning an interesting challenge. Here I give three very different examples:
Handling non-analyticity of finite-time transitions in stochastic processes.
Learning and inference in generative models and fair representations.
Small shot learning through learning transfer.
I introduce the problems and the methods that can be used, and discuss the open practical and mathematical challenges.