| Current Talks | • Combining Local Symmetry Exploitation and Reinforcement Learning for Optimised Probabilistic Inference. DSO-24 6th Data Science Meets Optimisation Workshop at IJCAI-24, Jeju Link to event |
| Current Publications | • Hamid, Sagad; Braun, Tanya Combining Local Symmetry Exploitation and Reinforcement Learning for Optimised Probabilistic Inference - A Work In Progress. , 2025 online • Lee D; Kong M; Hamid S; Lee C; Yoo J Aggregation Buffer: Revisiting DropEdge with a New Parameter Block. Proceedings of the 42nd International Conference on Machine LearningProceedings of Machine Learning Research Vol. 267, 2025, pp 33181-33204 online • Molchanov V, Hamid S, Linsen L Efficient Morphing of Shape-preserving Star Coordinates. 2020 IEEE Pacific Visualization Symposium (PacificVis), 2020, pp 136-145 online • Hamid S, Derstroff A, Klemm S, Ngo Q. Q., Jiang X, Linsen L Visual ensemble analysis to study the influence of hyper-parameters on training deep neural networks. Machine Learning Methods in Visualisation for Big Data, 2019 online | sagad dot hamid at uni-muenster dot de |
| Phone | +49 251 83-33094 |
| Room | 608a |
| Secretary | Sekretariat Steinhoff Frau Gerlinde Steinhoff Telefon +49 251 83-38447 Zimmer 602 |
| Address | Herr Sagad Hamid Institut für Informatik Fachbereich Mathematik und Informatik der Universität Münster Einsteinstrasse 62 48149 Münster Deutschland |
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