Seminar (Hauptstudium)
Seminar Graphische Modelle
PD Dr. Volker Steinhage
Graphical models are a marriage between probability theory and graph theory. They provide a natural tool for dealing with two problems that occur throughout applied mathematics and engineering - uncertainty and complexity - and in particular they are playing an increasingly important role in the design and analysis of machine learning algorithms. Fundamental to the idea of a graphical model is the notion of modularity - a complex system is built by combining simpler parts. Probability theory provides the glue whereby the parts are combined, ensuring that the system as a whole is consistent, and providing ways to interface models to data. The graph theoretic side of graphical models provides both an intuitively appealing interface by which humans can model highly-interacting sets of variables as well as a data structure that lends itself naturally to the design of efficient general-purpose algorithms. Michael Jordan, 1998
| Zeit, Ort | Mi, 9-11, A 121 |
| Beginn | 20.10.2004 (1. Gruppentreffen) |
| Vorbesprechung | Mi, 13.10.2004, 17:00, A 207. |
| Teilnehmerzahl | 12 |
| Vortragsmodus | Einzelvortrag + schriftliche Ausarbeitung |
| Voraussetzungen | Vordiplom | | Nachfolgeveranstaltungen | Seminare, Praktika im Bereich KI, Bildverstehen, Robotik |
| Bereich (alte DPO) | B |
| Bereich (neue DPO) | B |
| Literatur | Michael Jordan: Learning in Graphical Models. MIT Press, 1999. |
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Übersicht: alle Semester
Methoden des Bildverstehens
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