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Computer Science > Machine Learning

arXiv:2206.13446 (cs)
[Submitted on 27 Jun 2022]

Title:Pen and Paper Exercises in Machine Learning

Authors:Michael U. Gutmann
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    Abstract: This is a collection of (mostly) pen-and-paper
    exercises in machine learning. The exercises are on the following
    topics: linear algebra, optimisation, directed graphical models,
    undirected graphical models, expressive power of graphical
    models, factor graphs and message passing, inference for hidden
    Markov models, model-based learning (including ICA and
    unnormalised models), sampling and Monte-Carlo integration, and
    variational inference.

Comments: The associated github page is this https URL
Subjects: Machine Learning (cs.LG); Machine Learning (stat.ML)
Cite as:  arXiv:2206.13446 [cs.LG]
          (or arXiv:2206.13446v1 [cs.LG] for this version)
          https://doi.org/10.48550/arXiv.2206.13446
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Michael Gutmann [view email]
[v1] Mon, 27 Jun 2022 16:53:18 UTC (1,679 KB)
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