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Now You See Me (CME): Concept-based Model Extraction
https://mlg.eng.cam.ac.uk/adrian/AIMLAI20-CME.pdf19 Jun 2024: Model ExtractionModel extraction techniques use rules [20, 21, 22], de-cision trees [23, 24], or other more readily explainablemodels [25] to approximate complex models, in orderto study their behaviour. ... 24] M. Sato, H. Tsukimoto, Rule extraction -
ICML-Presentation
https://mlg.eng.cam.ac.uk/zoubin/talks/ICML-Presentation.pdf27 Jan 2023: International Conference onMachine Learning. Corvallis, Oregon, June 20-24 2007. Summary Presentation:Statistics, Awards, Comments. -
- 4F13: Machine Learning
https://mlg.eng.cam.ac.uk/teaching/4f13/1011/lect01.pdf19 Nov 2023: Ghahramani & Rasmussen (CUED) Lecture 1: Introduction to Machine Learning 24 / 26. -
Unsupervised Learning Lecture 6: Hierarchical and Nonlinear Models…
https://mlg.eng.cam.ac.uk/zoubin/course03/lect6hier.pdf27 Jan 2023: Annual Review of. Neuroscience, 24. Applications of ICA and Related Methods. • -
- 4F13: Machine Learning
https://mlg.eng.cam.ac.uk/teaching/4f13/1011/lect07.pdf19 Nov 2023: But we can not usually simulate Hamiltonian dynamics exactly. Ghahramani & Rasmussen (CUED) Lecture 7 and 8: Markov Chain Monte Carlo 24 / 28. -
- Machine Learning 4F13, Michaelmas 2015
https://mlg.eng.cam.ac.uk/teaching/4f13/1516/lect0304.pdf19 Nov 2023: 1 0 1 22. 1. 0. 1. 2M=0. 1 0 1 24. ... 1. 2M=0. 1 0 1 24. 2. 0. 2. 4. M=1. -
chuesann.dvi
https://mlg.eng.cam.ac.uk/pub/pdf/ChuGhaWil04b.pdf13 Feb 2023: H70.13% 70.77% 72.28% 71.70%. QobsE. 46.51% 24.69% 46.86% 23.96%Qobs. C73.29% 70.52% 72.64% 70.86%. -
- Machine Learning 4F13, Spring 2014
https://mlg.eng.cam.ac.uk/teaching/4f13/1314/lect0304.pdf19 Nov 2023: 1. 0. 1. 2M=0. 1 0 1 24. 2. 0. 2. ... 1. 2M=0. 1 0 1 24. 2. 0. 2. 4. M=1. -
nips.dvi
https://mlg.eng.cam.ac.uk/pub/pdf/Ras96.pdf13 Feb 2023: 0.2. 0.3. 0.4. 0.5. 0.6. House. 24 48 96 1920. 0.05. -
- Machine Learning 4F13, Spring 2015
https://mlg.eng.cam.ac.uk/teaching/4f13/1415/lect0304.pdf19 Nov 2023: 1. 0. 1. 2M=0. 1 0 1 24. 2. 0. 2. ... 1. 2M=0. 1 0 1 24. 2. 0. 2. 4. M=1.
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