AaltoDictionaryofML

📘 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.

---

📥 Download

• 📘 English PDF (latest release)
• 🌐 Translations
  (Spanish, German, French, Greek, Finnish)

---

📈 Interactive Term Network

Explore relationships between terms:
👉 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 — Fork the Repository

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

Step 2 — Clone Your Fork

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

Step 3 — Create a New Branch

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

---

Step 4 — 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 — Commit and Push

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

---

Step 6 — Open a Pull Request

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

---

💡 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.

---

🧑‍🤝‍🧑 Authors & Contributors

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

Contributors:

• Konstantina Olioumtsevits — Aalto University
• Ekkehard Schnoor — Aalto University
• Tommi Flores Ryynänen — Aalto University
• Juliette Gronier — ENS Lyon
• Salvatore Rastelli — Aalto University

Full contributor list: AUTHORS.md

---

💰 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.

---

📌 Citation

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

Jung, A., Olioumtsevits, K., Schnoor, E., Flores Ryynänen, 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

• GitHub: AaltoDictionaryofML.github.io
• Zenodo DOI: 10.5281/zenodo.17273736
• Springer MRW: Dictionary of Applied Machine Learning (forthcoming)

---

This site is open source. Improve this page.