News
Practice talks: an option to finish before ChristmasWritten on 06.11.26 by Noa Izsak Dear all, In Session 2, several of you asked whether the practice talks could end before the Christmas break. This is possible if a few of you are willing to give your practice talk early, on Friday, 20 November. How it would work
Dear all, In Session 2, several of you asked whether the practice talks could end before the Christmas break. This is possible if a few of you are willing to give your practice talk early, on Friday, 20 November. How it would work
Why it can be worth it
If it takes place, 20 November is a regular session for everyone, in place of 18 December. If you would like to present on 20 November, please write to me by e-mail by Thursday, 12 November. By our third session, we will let everyone know whether the session on 20 November takes place. Best regards, |
Proseminar Automata Learning: room change (0.02 from now on)Written on 02.11.26 by Noa Izsak A quick note about the room for the rest of the semester:
From now on, our sessions will take place in Building C0, room 0.02 (the "Showroom"), instead of room 0.01. Time and day stay the same: Fridays, 10-12 c.t. (we start at 10:15).
Good news: from the entrance lobby, 0.02 is… Read more A quick note about the room for the rest of the semester:
From now on, our sessions will take place in Building C0, room 0.02 (the "Showroom"), instead of room 0.01. Time and day stay the same: Fridays, 10-12 c.t. (we start at 10:15).
Good news: from the entrance lobby, 0.02 is the room on your right, so there's no need to walk through it to get anywhere anymore :)
See you on Friday! |
Proseminar Automata Learning: how to find room 0.01Written on 30.10.26 (last change on 02.11.26) by Noa Izsak A quick note on finding the room for today's session, since it can be a little confusing if you haven't been to Building C0 before: Room 0.01 is reached through room 0.02. From the entrance lobby, go into the room on your right (0.02) and walk through it to get to 0.01. See you soon! |
First session: tomorrow, Fri 30 OctWritten on 29.10.26 (last change on 02.11.26) by Noa Izsak The first session of the Proseminar "Automata Learning: Learnability of Computational Models" takes place tomorrow: Fri 30 Oct 2026, 10 - 12 c.t. (we start at 10:15) In this session we explain how the seminar works (talks, grading, dates), how the topic list is organized… Read more The first session of the Proseminar "Automata Learning: Learnability of Computational Models" takes place tomorrow: Fri 30 Oct 2026, 10 - 12 c.t. (we start at 10:15) In this session we explain how the seminar works (talks, grading, dates), how the topic list is organized and how you choose your topic, and we begin the background material that every talk builds on. You do not need to prepare anything. Attendance in this seminar is mandatory; we explain the exact rule tomorrow. The full topic list will be on CMS by Mon 2 Nov at the latest. See you tomorrow! |
Proseminar, Winter Term 2026/27
Your IDE highlights a syntax error the moment you type it. Your compiler knows that the parentheses are unbalanced before you even run the program. These tools know the rules of the language -- but how did they get that knowledge? In most cases, the rules were written by hand. But what if they weren't? What if a system could figure out the rules just by observing examples?
This is the central question of automata learning: given labeled examples of instances that belong (or do not belong) to some unknown language, can we automatically reconstruct a compact, correct model of it?
The idea may feel familiar to many of you, coming from different directions. In machine learning, the goal is also to recover a hidden model from labeled instances. In security, an adversary observing the inputs and outputs of a black-box system is trying to reverse-engineer what is happening inside. In software testing, a tool that infers a model of a protocol from observed network traces can then check whether the implementation behaves correctly. These are all instances of the same underlying problem.
In this seminar, we study the problem from a theoretical angle. We ask and answer four recurring questions about different classes of computational models: Can we always infer a correct model from a labeled sample? Is finding the smallest consistent model computationally tractable? How much data do we need to guarantee correct learning? And can we learn efficiently by asking questions, rather than passively receiving examples?
During this class, students will learn how to read a scientific text and how to give a scientific presentation. Each student reads up on an assigned topic and teaches the results to their fellow students.
Talks: We expect you to give two talks on your assigned topic: an ungraded short practice talk, after which you will receive detailed feedback, and a graded final talk of 30 minutes.
Feedback and Discussion: Attendance at all talks is mandatory. We expect you to provide feedback to your fellow students after the practice talks and to participate in discussions after the final talks.
Requirements: We expect you to be comfortable with basic mathematical reasoning and to have the ability to think about abstract concepts. Some familiarity with automata and formal languages is helpful, but we will cover all necessary background in the first sessions.
Course Materials: De la Higuera, Colin, Grammatical inference: Learning automata and grammars Cambridge University Press 2010