[AI-announce] Courses of the research group "Logic and Formal Verification" in winter term 23/24

[Kerstin Kallweit]

Liebe AI-Studierende,

bezugnehmend auf die Mail von Herrn Zeume möchte ich darauf hinweisen, 
dass der Masterkurs "Computational complexity theory" (aka 
"Komplexitätstheorie") ab dem WS 23/24 nicht mehr im Wahlpflichtkatalog 
der Angewandten Informatik gelistet ist. Bei Interesse kann das Modul 
als Freies Wahlfach im Master belegt werden.

Auch das aufgeführte Masterseminar ist nicht für Studierende der AI 
belegbar.

Viele Grüße,

Kerstin Kallweit

Am 18.09.23 um 10:23 schrieb Thomas Zeume via AI-announce:
> Dear students,
>
> Soon the winter term 2023/2024 will start and I would like to draw 
> your attention to the courses offered by our research group.
>
> ## Bachelor lecture "Logik in der Informatik".
>
> Lecture: Mondays 10:00 - 12:00, room HGB 10 (first lecture: 09.10.2023)
> https://moodle.ruhr-uni-bochum.de/enrol/index.php?id=53920
>
>
> ## Master lecture "Computational complexity theory"
> Lecture: Tuesdays and Thursdays, 10:00 - 12:00, Room MC 1.54 (first 
> lecture: 10.10.2023)
> https://moodle.ruhr-uni-bochum.de/enrol/index.php?id=53919
>
>
> ## Bachelor seminar "Perlen der theoretischen Informatik"
> Registration has already closed.
>
>
> ## Master seminar "Learning and Formal Methods"
> This seminar is at the interface of AI, formal methods and theoretical 
> computer science.  It is a joint seminar with Prof. Dr. Daniel Neider 
> (Verification and Formal Guarantees of Machine Learning) and Prof. Dr. 
> Jean Jung (Knowledge-Based Systems) at TU Dortmund. See below for more 
> information on content.
>
> Dates:
> - Introduction session: 11.10.2023; 10 am
> - Talks: en bloc in the week 5.2.2024 - 9.2.2024
>
> Registration: via email to me (thomas.zeume at rub.de)
>
>
>
> I wish you a good start to the winter term!
>
> Best wishes,
> Thomas Zeume
>
>
> Seminar "Learning and Formal Methods"
>
> Abstract: In this seminar we will explore recent advances in  how (1) 
> formal descriptions and models can be learned from data; and how (2) 
> methods from theoretical computer science can be used to understand 
> the power of models used in machine learning, such as (graph) neural 
> networks.
>
> Learning formal descriptions and models from data has many 
> applications in areas such as formal verification, databases, 
> artificial intelligence, and knowledge representation. A typical 
> challenge in these areas is to design algorithms that learn logical 
> formulas, queries, or specifications from user-provided data.
>
> On the other hand, theoretical computer science provides the means to 
> understand the power of typical models used in machine learning. For 
> example, the power of graph neural networks has recently been related 
> to the computational power of classes of circuits and to the 
> expressive power of logics.
>
> In the seminar, we will survey the recent literature on these aspects. 
> Most topics will be of rather theoretical nature (in the sense of 
> theoretical computer science), but there will also be some more 
> practical topics.
>
> The seminar is aimed at Master students of Computer Science, ITS, and 
> Mathematics.
>
>
-- 
Dipl.-Biol. Kerstin Kallweit
*Ruhr-Universität Bochum *
*Fakultät für Informatik / Studienfachberatung Angewandte Informatik *
MC 1/36
Postfach 1 / Dekanat
Tel.: 0234/32-27685
Dienstzeiten: Mo, Mi und Do 7:30-16 Uhr; Di* und Fr* 7:30-12:30 Uhr
*HomeOffice
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