Machine Learning for Graphs and Sequential Data (IN2323)
Course 0000002444 in SS 2020
General Data
| Course Type | lecture with integrated exercises |
|---|---|
| Semester Weekly Hours | 4 SWS |
| Organisational Unit | Informatics 3 - Chair of database systems (Prof. Kemper) |
| Lecturers |
Bertrand Charpentier Stephan Günnemann Marten Lienen Oleksandr Shchur |
| Dates |
Wed, 14:00–16:00, virtuell Thu, 14:00–16:00, virtuell |
Assignment to Modules
-
IN2323: Machine Learning for Graphs and Sequential Data / Machine Learning for Graphs and Sequential Data
This module is included in the following catalogs:- Focus Area Imaging in M.Sc. Biomedical Engineering and Medical Physics
Further Information
Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.
| additional remarks | * Introduction - Machine Learning, Data Mining Process - Basic Terminology * Scalability - Similarity Estimation - Filter-Refine Paradigm - Hashing & Sketches - Min-Hashing - Locality Sensitive Hashing - Membership Test / Bloom Filter - Large-Scale Optimization * Temporal Data & Sequences - Autoregressive Models - HMMs - Embeddings (e.g. Word2Vec) - Neural Networks (e.g. RNN, LSTM) * Graphs & Networks - Laws, Patterns - (Deep) Generative Models - VAE, Implicit Models - Generative Models for Graphs - Spectral Methods - Ranking (e.g., PageRank, HITS) - Community Detection - Representation Learning for Graphs - Graph Neural Networks - (Unsupervised) Node Embeddings |
|---|---|
| Links |
Course documents E-Learning course (e. g. Moodle) TUMonline entry |
Equivalent Courses (e. g. in other semesters)
| Semester | Title | Lecturers | Dates |
|---|---|---|---|
| SS 2024 | Machine Learning for Graphs and Sequential Data (IN2323) | Gao, N. Gosch, L. Günnemann, S. Kollovieh, M. Kosmala, A. … (total 8) |
Wed, 14:00–16:00, Interims I 101 Thu, 14:00–16:00, Interims I 101 |
| SS 2023 | Machine Learning for Graphs and Sequential Data (IN2323) | Fuchsgruber, D. Günnemann, S. Scholten, Y. Schuchardt, J. Sommer, J. |
Wed, 14:00–16:00, Interims I 101 Thu, 14:00–16:00, Interims I 101 Wed, 14:00–16:00, online |
| SS 2022 | Machine Learning for Graphs and Sequential Data (IN2323) | Bilos, M. Gasteiger, J. Gosch, L. Günnemann, S. Hetzel, L. … (total 8) |
Wed, 14:00–16:00, Interims I 101 Thu, 14:00–16:00, Interims I 101 |
| SS 2021 | Machine Learning for Graphs and Sequential Data (IN2323) | Bilos, M. Charpentier, B. Günnemann, S. Lienen, M. Shchur, O. |
Thu, 14:00–16:00, virtuell Wed, 14:00–16:00, virtuell and singular or moved dates |
| SS 2019 | Mining Massive Datasets (IN2323) |
Günnemann, S.
Assistants: Shchur, O. |
Wed, 14:00–16:00, Interims I 101 Thu, 14:00–16:00, Interims I 101 |
| SS 2018 | Mining Massive Datasets (IN2323) |
Günnemann, S.
Assistants: Shchur, O. |
Wed, 14:30–16:00, Interims I 101 Thu, 14:00–16:00, Interims I 101 and singular or moved dates |
| WS 2016/7 | Mining Massive Datasets (IN2323) | Günnemann, S. | |
| WS 2015/6 | Mining Massive Datasets (IN2323) |