[Submitted on 27 Jun 2022]
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The following is a collection (mostly) of pen-and paper exercises in machine learning. The exercises cover the following topics: linear algorthim, optimisations, directed graphical model, undirected graphical model, expressive power of graphical modeling, factor graphs, message passing, inferences for hidden Markov models (including ICA, unnormalised models), Monte-Carlo integration and sampling, and variational analysis.
Submission History
Michael Gutmann [view email]
[v1] Monday, 27 June 2022 16:53.18 UTC (1.67 KB)
