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KGA Slides

Here you find an outline of the lecture (order and topics might be adopted during the semester).
Slides will be added shortly before the upcoming class.

Date Chapter/Topic Slides (and date of last update)
18.10.16 01. Motivation 01-motivation.pdf
25.11.16 02. RDF Databases 02-rdfdatabases.pdf
01.11.16 - public holiday -
08.11.16 03. Property Graph Databases 03-propertygraphdatabases.pdf
15.11.16 04. Statistical relational learning 04-statistcalrelationallearning.pdf
22.11.16 05. Tensor-Factorization methods 05-tensors.pdf
29.11.16 06. Alternating Least Squares and Stochastic Gradient Descent 06-sgd_als.pdf
06.12.16 07. Introducing Neural Networks 07-neuralnetworks.pdf
13.12.16 - no lecture -
20.12.16 08. Neural Networks for KGA 08-nnsforkga.pdf
10.01.17 09. Latent Distance and Graph Feature models 09-ldandgfmodels.pdf
17.01.17 - no lecture -
24.01.17 10. Markov Logic Networks 11-mlns.pdf
31.01.17 11. Training SRL Models 10-trainingsrlmodels.pdf
07.02.17 12. Summary 12-summary.pdf

The Slides of the talk of our invited speaker Paul Groth can be found here:

Date Chapter/Topic Slides (and date of last update)
07.02.17 Knowledge Graph Analysis in Practice kg-analysis-elsevier-feb82017.pptx
teaching/lectures/kga/2016/slides.txt · Last modified: 2018/05/09 01:59 (external edit)

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