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Veranstaltungszeit: wird noch bekannt gegeben

Einschreibeschlüssel: folgt

Prof. Dr. Ulrich Becker, LL.M. (EHI) auf der Fakultätshomepage

Basic Information

• Language: English
• Prerequisite courses
  • Formal Languages and Complexity (must)
  • Logic and Discrete Structures (must)
  • Formal Specification and Verification (recommended)
  • Software Verification (recommended)
  • SAT Solving (recommended)
• Date: Thursday, 10:15-11:45
• Location: Seminar Room 133, Oettingenstr. 67
• First meeting: 2024-04-18 (about the detailed seminar organization and expectations)

Content

Model checking is an important research field in computer science where automatic solutions to the following problem are studied: Given a computational model and a specification, decide whether the model satisfies the specification or not. In practice, a computational model can be a digital circuit (hardware) or a program (software). A specification can be a safety property requiring that errors never happen during the execution of the model. Compared to testing, model checking can guarantee the correctness of a computational model with mathematical rigor. Model checking is rooted in a solid theoretical foundation and requires advanced software engineering for tool implementation. The inventors of model checking won the 2007 Turing Award, and leading technology companies use model-checking techniques to assure the quality of their products.

Goal

The goal of this seminar is to learn the mathematical foundation and understand the working of state-of-the-art algorithms for hardware and software model checking. At the end of this seminar, students should become familiar with the background knowledge of model checking and able to explain a scientific publication on model checking in oral and written forms.

Organization

The seminar will consist of three phases:

1. Reading sessions: In the first phase, we will recap the mathematical foundation of model checking. Students will be divided into groups. Each group will be assigned a topic and lead the discussion on the topic in one seminar session.
2. Weekly meetings: In the second phase, each student will be assigned a publication on an algorithm for model checking. Students will have weekly meetings with the mentors to report their progress. Mentors will guide students to read and understand the algorithms in the publications.
3. Final presentation and report: In the final phase, students will present the algorithms assigned to them and write a report explaining them with examples and analysis.

Team

• Prof. Dr. Dirk Beyer
• Nian-Ze Lee, Ph.D.
• Po-Chun Chien

References

• Handbook of Model Checking, 2018

Anmeldung

Die Anmeldung zu diesem Seminar erfolgt über die Zentralanmeldung für Bachelorseminare.

Voraussetzung für das Seminar ist die erfolgreiche Teilnahme an der Veranstaltung Algorithmen und Datenstrukturen!

Immer öfter begegnet man seit einiger Zeit Daten mit funktionalem Charakter, für die jede Beobachtung eine Kurve darstellt. Beispiele reichen von der Ökonometrie oder Meteorologie, wo gewisse Größen kontinuierlich über die Zeit erhoben werden, bis zu Absorptionsspektren von infrarotem Licht in der Chemometrie. Statt Messungen dieser Kurven an diskreten Punkten als einzelne Variablen aufzufassen, empfiehlt es sich bei der Analyse dieser Art von Daten auf deren speziellen funktionalen Charakter Rücksicht zu nehmen und diesen gewinnbringend zu nutzen.

Im Seminar werden nun eine Reihe von Verfahren vorgestellt und untersucht, die speziell auf funktionale Daten zugeschnitten sind. Dabei werden sowohl (inzwischen) etablierte Techniken behandelt als auch neuere Ansätze diskutiert.

Vorbesprechung: 20.10.2017, 12:30 Uhr s.t.

Any questions please email to yunru.wang@ifi.lmu.de

Time & Location：

Thursdays 16:00-18:00, Room U 133, Oettingenstr. 67

Introduction：

In this seminar, we will delve into the development of ML techniques for code semantic representation. Tracing its evolution from applying traditional ML algorithms to large language models, as well as the shift from manual feature engineering to self-supervised tasks and neural networks specifically designed for code semantics.

This seminar aims to deepen your understanding of code semantics and neural networks through discussions and coding practices.

• in English
• Attendance at the first session (18-04-2024) is mandatory.
  
• Interest in binary analysis and a basic knowledge of machine learning.
  

This seminar offers a variety of topics from High Performance Computing, Quantum Computing, Virtual Reality and Cryptography for students to work on.

Each participant will work on one topic throughout the semester (master students on their own, bachelor students in pairs). The goal is to write a paper, submit it to an imaginary conference committee, review each other's work and present their findings at an end-of-term "conference" in the seminar.

The task is supported by a lecture about scientific writing and presentations and by an individual supervisor for each topic.

The mandatory lectures will take place on Wednesday 17.04.24 and 08.05.24, 12-14 h c.t., room 061 in Oettingenstr. 67.
The exam date will be Saturday 06.07.24, 9-18 h, room B001 in Oettingenstr. 67.

Dependent type theories are formal systems which can be understood both as powerful logics and functional programming languages. They have been studied since the late 1960’s and today serve as the foundations of popular interactive theorem provers such as Agda, Coq, Idris and Lean. In this seminar, we will discuss various important type theories and their properties.

You can register for this seminar only via the central allocation of MSc seminars.

Die Texte der Urgeschichte (Gen 1–11) zählen zu den theologisch anspruchsvollsten und wirkmächtigsten des Alten Testaments. Sie führen nicht nur in aktuelle Debatten (von Kreationismus bis Erbsündenlehre), sondern waren und sind Gegenstand einer vielgestaltigen und verzweigten Auslegungsgeschichte. Insbesondere in der altkirchlichen Auslegung wurden dabei Weichen gestellt, die die kirchliche Lehrentwicklung zu entscheidenden Fragen wie z.B. dem Gottes- oder Menschenbild tiefgreifend prägte und  die Rezeption bis in die gegenwärtigen Debatten hinein beeinflusst.

Contents of seminars

• the human genome project
• CRISPR/Cas
• fingerprinting
• personalized medicine
• pre-implantation diagnostics
• ExAc project
• epigenetics
• 24 and me

Skills

• presentation skills
• literature search and evaluation
• design of scientific questions
• literature-based argumentation
• moderation of discussions

Gödel's incompleteness theorems are celebrated results in mathematical logic that significantly impact on computing. A seminar's first aim is to get a grasp of Gödel's incompleteness theorems' proofs. A seminar's second aim ist to directly approach Gödel's incompleteness theorems from Gödel's article of 1938, helped if needed from introduction to (modern version of) the proofs of Gödel's incompleteness theorems. The seminar's third and last aim ist to grasp the meaning of Gödel's incompleteness theorems - and to debunk some widespread esoteric "understandings" of these theorems. 

Die Weimarer Republik ist aus jüdischer Sicht im Rückblick höchst ambivalent zu bewerten. Zum einen waren nun rechtliche Beschränkungen mit der Einführung der Demokratie nun endgültig aufgehoben. Die deutsch-jüdische Kultur erlebte eine Renaissance und durch die Einwanderung von Juden aus Ostereuropa entstanden vielerorts neue Lehrzentren. Gleichzeitig wurde die Republik selbst von vielen Krisen gebeutelt, die sich auch auf deren jüdischen Staatsbürger auswirkten. Zudem erlebte auch der Antisemitismus neuen Auftrieb und innerjüdische Spannungen um politische Fragen wie den Zionismus oder zwischen deutschen Juden und sogenannten „Ostjuden“ verschärften sich. Nicht zuletzt erlebte die Weimarer Republik Gründung und Aufstieg der Nationalsozialisten, die das politische und gesellschaftliche Klima immer stärker beeinflussten. Dennoch wäre es verkürzt, jüdische Geschichte in der Weimarer Republik lediglich als ein Vorkapitel zum NS und schließlich der Vernichtung des europäischen Judentums zu begreifen. Der Kurs widmet sich den verschiedenen Facetten jüdischen Lebens in der Weimarer Republik anhand der Sekundärliteratur und einer weiten Bandbreite an historischen Quellen.   

Prüfungsformen im BA und LA (Studienbeginn bis SOSE 2020): KL+RE+HA

Achtung NEU!

Prüfungsformen im BA und LA (Studienbeginn ab WISE 2020/21): RE + HA

Prüfungsform im Didaktikfach - Mittelschule und Sonderpädagogik (Studienbeginn ab WISE 2015/16):  RE + HA

This seminar covers recent topics and advances in Reverse Engineering techniques aided by Machine Learning. We will cover recovery of function boundaries, symbols, and in particular Deep Learning models that produce vector representations of machine code.

Participants should have basic knowledge in Machine Learning and should be somewhat familiar with assembly code.

Participation in the first session (April 17) is mandatory, anyone not present (without valid excuse) cannot take this seminar. Seminar sessions take place Wednesdays 4pm-6pm at Oettingenstr. 67, room 033 from 17.4.-17.7.24

After the first session, the participants will choose their paper. The first presentations start two weeks after. Each participant is required to give a presentation of his paper, prepare a discussion, participate in every week's discussion, and write a seminar report at the end of the term.

Malware (d.h. Viren, Trojaner und Würmer) entwickelt sich stetig weiter. Waren die ersten Viren in den 1970er Jahren noch eher vereinzelte Experimente, schafften es in den 90er Jahren einige Schadprogramme in die Medien, bevor sich in den 2000ern vor allem E-Mail-Würmer explosionsartig ausbreiten konnten. Mittlerweile dominieren kriminelle Organisationen und Geheimdienste das Geschehen und entwickeln hochspezialisierte Malware, von Verschlüsselungs-Trojanern zur Erpressung von Lösegeldern bis zu unauffälligen Hintertüren für Spionage und Sabotage.

In diesem Seminar betrachten wir sowohl die historische Entwicklung von Malware als auch aktuelle Trends. Verfügbare Themen werden akademische Arbeiten zur Malware-Analyse und Erkennung sein, aber auch detaillierte Berichte zu einzelnen prominenten Malware Exemplaren.

Voraussetzung für das Seminar ist ein Interesse für Maschinencode und Details von Betriebssystemen.

Neben den eigentlichem Inhalt sollen auch Grundlagen des wissenschaftlichen Arbeitens vermittelt werden.

Seminar: Mechanisms of plant gene regulation by Prof. Dr. Wolfgang Frank and Dr. Oguz Top

Content

Learning outcomes

Some algorithms from machine learning have successfully approached many of the problems that seemed unsolvable a few decades ago (eg. computer vision, image generation). Irrespective of the successes in applied settings, the learning process, as well as the uncertainties that underlie the learning, remain open problems that challenge the foundations of statistics. Since attempts relying on the traditional (Bayesian and frequentist) frameworks have shown only limited success, some researchers have directed their efforts in questioning the foundations of statistics in a very principled manner (eg. What if there is no data generating process? What if we are not certain about our prior beliefs? Can we talk about a conditional distribution of the parameters without imposing a prior on the parameters? Are all uncertainty dimensions covered?).
In this seminar, we will explore foundations rooted in five main blocks, namely: traditional Bayesian and frequentist frameworks, imprecise probability, decision theory, information theory and compression algorithms. We will build on the following non-exhaustive list of papers:

1. Aleatoric and epistemic uncertainty in machine learning: An introduction to concepts and methods - Hüllermeier, Waegeman (2021)
2. Sources of Uncertainty in Machine Learning--A Statisticians' View - Gruber et al. (2023)
3. Minimum description length revisited - Grünwald and Roos (2020)
4. The Interplay of Bayesian and Frequentist Analysis - Bayarri and Berger (2004)
5. Robust Bayesian Analysis: sensitivity to prior - Berger (1987)
6. All models are wrong, but many are useful: Learning a variable's importance by studying an entire class of prediction models simultaneously - Fisher et al. (2019)
7. Strictly frequentist imprecise probability - Fröhlich et al. (2024)
8. Information-theoretic upper and lower bounds for statistical estimation - Zhang (2006)
9. The E-Posterior - Grünwald (2023)
10. How the game-theoretic foundation for probability resolves the Bayesian vs. frequentist standoff? - Shafer (2020)
11. Judicious Judgement Meets Unsettling Updating: Dilation, Sure Loss and Simpson’s Paradox - Gong and Meng (2021)
12. Testing by betting: A strategy for statistical and scientific communication - Shafer (2019)


We invite students to suggest their own papers that fit within the topic as well.


Who is this seminar for: Motivated students who are open to explore current trends in the foundations of statistics that might provide tools to solve open problems in uncertainty quantification and learning. The seminar is open to master’s students from statistics, mathematics, economics, data science, and similar backgrounds. For students of the Statistics and Data Science program, the seminar can be recognized for the mandatory seminar module in the Methodology & Modeling, Machine Learning and Social Statistics and Data Science tracks, as well as for the additional elective general seminar module ‘Advanced Research Methods in Theoretical Statistics’ (WP 51).

Data Science tracks, as well as for the additional elective general seminar module ‘Advanced Research Methods in Theoretical Statistics’ (WP 51). Requirements for obtaining 9 ECTS credits: Every student has to
* give a 45-60 minutes long presentation on their chosen topic supported by slides and
* write a seminar paper based on it (As a rough guideline: the typical seminar paper is 25-30 pages long; in case the paper is very technical, it can be considerably shorter, which is to be agreed on with the organisers of the seminar). The paper has to be submitted by 01.06.2025 and shall contain a deepened and extended version of the presentation, also taking up the discussion of the presentation and positioning the chosen topic in the context of the seminar. (The registration for the 9 ECTS has to be done via LSF.)

If places are left, we are happy to offer in addition a 3 ECTS version, based on a shorter term paper or presentation. The 3 ECTS could be used flexibly for one of the corresponding generic modules. To apply for the 3 ECTS option write an email to ivan.melev@lmu.de no later than September 25 (no registration via LSF!).

We expect active participation in the discussions of the seminar. This includes a quick personal preparation for each presentation based on some preparation material (1 page) the speakers are asked to provide one week in advance.

What is the format? This is a block seminar in a face-to-face format. It will take place during the week of 26.02.2025-28.02.2025; the exact dates are still to be decided.

Content

A good amount of software-engineering research consists of the creation of software or its analysis. The software and data that are created by researchers in this process are referred to as "research artifacts". These artifacts are useful in two ways. First, other researchers can reproduce the reported research results. That means that, in theory, anyone having access to the research artifact should be able to observe the same results as reported by the researchers. Second, other researchers can reuse these artifacts in their own research.

The goal of this seminar is to learn how to use and assess artifacts from software engineering and programming language research.

In this process students will acquire basic skills for conducting reproducible scientific re­search, which will be useful for their final projects and further academic careers. They will learn how to perform a reproduction study, document their work, write a report, and present their findings.

Students will perform a reproduction study on a given set of already published artifacts. Their main tasks are to

• verify that published research artifacts are still available and usable,
• read the related publications,
• follow the documentation of the artifacts to reproduce the studies' results, and
• report the findings.

Team

• Prof. Dr. Dirk Beyer
• Dr. Stefan Winter
  
• Marian Lingsch-Rosenfeld

Process

This presence course will consist of 3 phases.

1. Reading lectures: four presence sessions (one per week) in which students will read and discuss relevant publications on artifact evaluation to gain knowledge on the topic and relevant skills to perform the reproduction study.

2. Reproduction study: independent work in which each student is given a set of publications with artifacts. Students will document their independent work in lab reports and present the individual reproduction results. A weekly office hour will be offered for discussions on practical issues that students may be facing.

3. Report and presentation: Students will write a final report based on their experimental work documented in the lab report from phase 2. Additionally, they will prepare a 10 minutes presentation.

Requirements

Students should be interested in reading and understanding scientific publications. A healthy degree of scepticism is beneficial.

This seminar is in English.

Die Einschreibung für den Moodle-Kurs Seminare Pharmazeutische Technologie gilt immer für ein Semester.

Den Einschreibeschlüssel für den Moodle-Kurs für das aktuelle Semester erhalten Sie automatisch, wenn Sie sich für das Seminar Biopharmazie im LSF angemeldet haben.

Die Anmeldung für diese Seminare findet bis zum 31.03.2026 über LSF statt. Nähere Informationen zur Anmeldung finden Sie bei den jeweiligen Studiengängen unter https://www.cup.lmu.de/de/studiengaenge/.