Eilers, Pieter Jan (2020) On-line Learning under Concept Drift. Master's Internship Report, Computing Science.
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Abstract
Using a modeling framework for the purpose of investigating on-line learning processes in non-stationary environments, we conduct experiments for a number of different situations. We consider the learning of a regression scheme in layered neural networks using sigmoidal and ReLU activation. In all situations, the target, i.e. the regression scheme, changes continuously while the system is trained from a stream of input data. We run Monte Carlo simulations in Student-Teacher scenarios equal number of student and teacher units, K = M. We extend this to the overlearnable case, where K>M. We include weight decay as a from of explicit forgetting and study its effects with regards to drift.
| Item Type: | Thesis (Master's Internship Report) |
|---|---|
| Supervisor name: | Biehl, M. and Straat, M.J.C. |
| Degree programme: | Computing Science |
| Thesis type: | Master's Internship Report |
| Language: | English |
| Date Deposited: | 31 Jul 2020 13:34 |
| Last Modified: | 31 Jul 2020 13:34 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/22948 |
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