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Welcome! πŸ‘‹ This is the working draft of the Aalto Dictionary of Machine Learning (ADictML) β€” a growing collection of short, clear definitions for key terms in machine learning.

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πŸ“˜ Aalto Dictionary of Machine Learning (ADictML)

A multilingual, open-access glossary for mastering machine learning and AI terms.
Developed by the Aalto Machine Learning Group for students, researchers, and educators at Aalto University.


πŸ“₯ Download


πŸ“ˆ Interactive Term Network

Explore relationships between terms:
πŸ‘‰ View Glossary Network (HTML)

  • Terms are color-coded by semantic clusters
  • Hover for definitions, zoom and pan to explore

🧩 How to Contribute

We warmly welcome contributions from students, researchers, and educators worldwide!
Follow these steps to propose new entries, translations, or figure improvements.

Step 1 β€” Fork the Repository

  1. Visit the AaltoDictionaryofML GitHub repository.
  2. Click β€œFork” (top-right corner) to create your own copy under your GitHub account.

Step 2 β€” Clone Your Fork

git clone https://github.com/<your-username>/AaltoDictionaryofML.github.io.git
cd AaltoDictionaryofML.github.io

Step 3 β€” Create a New Branch

git checkout -b add-new-term-loss-function

Step 4 β€” Understand the Project Structure

All content is written in LaTeX and structured as follows:

File Purpose
ADictML_English.tex Front matter and main LaTeX driver. Loads macros, bibliography, and includes the main glossary file. Defines title page, TOC, and layout settings.
ADictML_Glossary_English.tex Main content file. Contains all English glossary entries, each created via \newglossaryentry{...}. Contributors usually edit this file when adding or revising terms.
/assets/ml_macros.tex Macro definitions. Provides standardized LaTeX commands for common ML notation (e.g. \lossfunc, \dataset, \feature, \weights, etc.). New entries should reuse these macros for consistency.
/assets/Literature.bib Bibliographic database. Contains BibTeX entries for textbooks, journal articles, and reports cited across entries. Use \cite{} commands to reference them.

Example of a glossary entry:

\newglossaryentry{optmethod}
{name={optimization method},
	description={An\index{optimization method} optimization method is an \gls{algorithm} that 
		reads in a representation of an \gls{optproblem} and delivers an (approximate) solution 
		as its output \cite{BoydConvexBook}, \cite{BertsekasNonLinProgr}, \cite{nesterov04}.
		 \\
		 See also: \gls{algorithm}, \gls{optproblem}.},
	first={optimization method},
	firstplural={optimization methods}, 
	plural={optimization methods}, 
	text={optimization method}
}

By default, all figures are created using TikZ code (see the TikZ & PGF Manual for guidance).


Step 5 β€” Commit and Push

git add .
git commit -m "Add glossary entry: Loss Function"
git push origin add-new-term-loss-function

Step 6 β€” Open a Pull Request

  1. Go to your fork on GitHub.
  2. Click β€œCompare & pull request.”
  3. Describe your contribution briefly and submit.
  4. The editorial team will review, comment, and merge upon approval.

πŸ’‘ Contribution Tips

  • Keep definitions concise (3–6 sentences).
  • Follow notation from /assets/ml_macros.tex.
  • Add cross-links via the see= field in \newglossaryentry.
  • When citing references, use keys from /assets/Literature.bib.
  • Discuss major new ideas via GitHub Issues.

πŸ§‘β€πŸ€β€πŸ§‘ Authors & Contributors

Editor-in-Chief:
Alexander Jung β€” Associate Professor, Aalto University
ORCID: 0000-0001-7538-0990

Contributors:

  • Konstantina Olioumtsevits β€” Aalto University
  • Ekkehard Schnoor β€” Aalto University
  • Tommi Flores RyynΓ€nen β€” Aalto University
  • Juliette Gronier β€” ENS Lyon
  • Salvatore Rastelli β€” Aalto University

Full contributor list: AUTHORS.md


πŸ’° Funding and Acknowledgements

The Aalto Dictionary of Machine Learning (ADictML) has been partially supported by:

  • XAI-based software-defined energy networks via packetized management for fossil fuel-free next-generation of industrial cyber-physical systems (X-SDEN) Research Council of Finland, Grant No. 349966
  • Mathematical Theory of Trustworthy Federated Learning (MATHFUL)
    Research Council of Finland, Grant No. 363624
  • TRUST-FELT – Trustworthy Federated Learning Technologies
    Jane and Aatos Erkko Foundation, Finland
  • FLAIG – AI Governance in Banking and Insurance
    Business Finland

These projects have enabled the open development of teaching materials, LaTeX figures,
and the public ADictML repository.

Funding: Research Council of Finland Funding: Research Council of Finland Funding: TRUST-FELT Funding: Business Finland


πŸ“Œ Citation

If you use or refer to ADictML, please cite as:

Jung, A., Olioumtsevits, K., Schnoor, E., Flores RyynΓ€nen, T., Gronier, J., & Rastelli, S. (2025).
Aalto Dictionary of Machine Learning (ADictML).
Aalto University. DOI: 10.5281/zenodo.17273736

A formal companion edition will appear in the Springer Dictionary of Applied Machine Learning (MRW).


🧾 License

This work is licensed under a Creative Commons Attribution–ShareAlike 4.0 International License.
See LICENSE for details.


🧭 Repository Links


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Welcome! πŸ‘‹ This is the working draft of the Aalto Dictionary of Machine Learning (ADictML) β€” a growing collection of short, clear definitions for key terms in machine learning.

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