Search result: Catalogue data in Autumn Semester 2018

Computer Science Master Information
Focus Courses
Focus Courses General Studies
Seminar in General Studies
NumberTitleTypeECTSHoursLecturers
252-4202-00LSeminar in Theoretical Computer Science Information
The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
W2 credits2SE. Welzl, B. Gärtner, M. Hoffmann, J. Lengler, A. Steger, B. Sudakov
AbstractPresentation of recent publications in theoretical computer science, including results by diploma, masters and doctoral candidates.
ObjectiveThe goal is to introduce students to current research, and to enable them to read, understand, and present scientific papers.
252-4601-00LCurrent Topics in Information Security Information Restricted registration - show details
Number of participants limited to 24.

The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
W2 credits2SD. Basin, S. Capkun, A. Perrig
AbstractThe seminar covers various topics in information security: security protocols (models, specification & verification), trust management, access control, non-interference, side-channel attacks, identity-based cryptography, host-based attack detection, anomaly detection in backbone networks, key-management for sensor networks.
ObjectiveThe main goals of the seminar are the independent study of scientific literature and assessment of its contributions as well as learning and practicing presentation techniques.
ContentThe seminar covers various topics in information security, including network security, cryptography and security protocols. The participants are expected to read a scientific paper and present it in a 35-40 min talk. At the beginning of the semester a short introduction to presentation techniques will be given.

Selected Topics

- security protocols: models, specification & verification
- trust management, access control and non-interference
- side-channel attacks
- identity-based cryptography
- host-based attack detection
- anomaly detection in backbone networks
- key-management for sensor networks
LiteratureThe reading list will be published on the course web site.
252-5051-00LAdvanced Topics in Machine Learning Information Restricted registration - show details
Number of participants limited to 40.

The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
W2 credits2SJ. M. Buhmann, A. Krause, G. Rätsch
AbstractIn this seminar, recent papers of the pattern recognition and machine learning literature are presented and discussed. Possible topics cover statistical models in computer vision, graphical models and machine learning.
ObjectiveThe seminar "Advanced Topics in Machine Learning" familiarizes students with recent developments in pattern recognition and machine learning. Original articles have to be presented and critically reviewed. The students will learn how to structure a scientific presentation in English which covers the key ideas of a scientific paper. An important goal of the seminar presentation is to summarize the essential ideas of the paper in sufficient depth while omitting details which are not essential for the understanding of the work. The presentation style will play an important role and should reach the level of professional scientific presentations.
ContentThe seminar will cover a number of recent papers which have emerged as important contributions to the pattern recognition and machine learning literature. The topics will vary from year to year but they are centered on methodological issues in machine learning like new learning algorithms, ensemble methods or new statistical models for machine learning applications. Frequently, papers are selected from computer vision or bioinformatics - two fields, which relies more and more on machine learning methodology and statistical models.
LiteratureThe papers will be presented in the first session of the seminar.
252-5701-00LAdvanced Topics in Computer Graphics and Vision Information Restricted registration - show details
Number of participants limited to 24.

The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
W2 credits2SM. Gross, M. Pollefeys, O. Sorkine Hornung
AbstractThis seminar covers advanced topics in computer graphics, such as modeling, rendering, animation, real-time graphics, physical simulation, and computational photography. Each time the course is offered, a collection of research papers is selected and each student presents one paper to the class and leads a discussion about the paper and related topics.
ObjectiveThe goal is to get an in-depth understanding of actual problems and research topics in the field of computer graphics as well as improve presentations and critical analysis skills.
ContentThis seminar covers advanced topics in computer graphics,
including both seminal research papers as well as the latest
research results. Each time the course is offered, a collection of
research papers are selected covering topics such as modeling,
rendering, animation, real-time graphics, physical simulation, and
computational photography. Each student presents one paper to the
class and leads a discussion about the paper and related topics.
All students read the papers and participate in the discussion.
Lecture notesno script
LiteratureIndividual research papers are selected each term. See Link for the current list.
Prerequisites / NoticePrerequisites:
The courses "Computer Graphics I and II" (GDV I & II) are recommended, but not mandatory.
263-2100-00LResearch Topics in Software Engineering Information Restricted registration - show details
Number of participants limited to 22.

The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
W2 credits2SZ. Su
AbstractThis seminar is an opportunity to become familiar with current research in software engineering and more generally with the methods and challenges of scientific research.
ObjectiveEach student will be asked to study some papers from the recent software engineering literature and review them. This is an exercise in critical review and analysis. Active participation is required (a presentation of a paper as well as participation in discussions).
ContentThe aim of this seminar is to introduce students to recent research results in the area of programming languages and software engineering. To accomplish that, students will study and present research papers in the area as well as participate in paper discussions. The papers will span topics in both theory and practice, including papers on program verification, program analysis, testing, programming language design, and development tools. A particular focus will be on domain-specific languages.
LiteratureThe publications to be presented will be announced on the seminar home page at least one week before the first session.
Prerequisites / NoticeOrganizational note: the seminar will meet only when there is a scheduled presentation. Please consult the seminar's home page for information.
263-2926-00LDeep Learning for Big Code Information Restricted registration - show details
Number of participants limited to 24.

The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
W2 credits2SV. Raychev
AbstractThe seminar covers some of the latest and most exciting developments (industrial and research) in the field of Deep Learning for Code, including new methods and latest systems, as well as open challenges and opportunities.
ObjectiveThe objective of the seminar is to:

- Introduce students to the field of Deep Learning for Big Code.

- Learn how machine learning models can be used to solve practical challenges in software engineering and programming beyond traditional methods.

- Highlight the latest research and work opportunities in industry and academia available on this topic.
ContentThe last 5 years have seen increased interest in applying advanced machine learning techniques such as deep learning to new kind of data: program code. As the size of open source code increases dramatically (over 980 billion lines of code written by humans), so comes the opportunity for new kind of deep probabilistic methods and commercial systems that leverage this data to revolutionize software creation and address hard problems not previously possible. Examples include: machines writing code, program de-obfuscation for security, code search, and many more.

Interestingly, this new type of data, unlike natural language and images, introduces technical challenges not typically encountered when working with standard datasets (e.g., images, videos, natural language), for instance, finding the right representation over which deep learning operates. This in turn has the potential to drive new kinds of machine learning models with broad applicability.

Because of this, there has been substantial interest over the last few years in both industry (e.g., companies such as Facebook starting, various start-ups in the space such as Link), academia (e.g., Link) and government agencies (e.g., DARPA) on using machine learning to automate various programming tasks.

In this seminar, we will cover some of the latest and most exciting developments in the field of Deep Learning for Code, including new methods and latest systems, as well as open challenges and opportunities.

The seminar is carried out as a set of presentations chosen from a list of available papers. The grade is determined as a function of the presentation, handling questions and answers, and participation.
Prerequisites / NoticeThe seminar is carried out as a set of presentations chosen from a list of available papers. The grade is determined as a function of the presentation, handling questions and answers, and participation.

The seminar is ideally suited for M.Sc. students in Computer Science.
263-2930-00LBlockchain Security Seminar Information Restricted registration - show details
Number of participants limited to 26.

The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
W2 credits2SP. Tsankov
AbstractThis seminar introduces students to the latest research trends in the field of blockchains.
ObjectiveThe objectives of this seminar are twofold: (1) learning about the blockchain platform, a prominent technology receiving a lot of attention in computer Science and economy and (2) learning to convey and present complex and technical concepts in simple terms, and in particular identifying the core idea underlying the technicalities.
ContentThis seminar introduces students to the latest research trends in the field of blockchains. The seminar covers the basics of blockchain technology, including motivation for decentralized currency, establishing trust between multiple parties using consensus algorithms, and smart contracts as a means to establish decentralized computation. It also covers security issues arising in blockchains and smart contracts as well as automated techniques for detecting vulnerabilities using programming language techniques.
263-3504-00LHardware Acceleration for Data Processing Information
The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
W2 credits2SG. Alonso, T. Hoefler, C. Zhang
AbstractThe seminar will cover topics related to data processing using new hardware in general and hardware accelerators (GPU, FPGA, specialized processors) in particular.
ObjectiveThe seminar will cover topics related to data processing using new hardware in general and hardware accelerators (GPU, FPGA, specialized processors) in particular.
ContentThe general application areas are big data and machine learning. The systems covered will include systems from computer architecture, high performance computing, data appliances, and data centers.
Prerequisites / NoticeStudents taking this seminar should have the necessary background in systems and low level programming.
263-3900-00LCommunication Networks Seminar Information Restricted registration - show details
Number of participants limited to 20.

The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
W2 credits2SA. Singla
AbstractWe explore recent advances in networking by reading high quality research papers, and discussing open research opportunities, most of which are suitable for students to later take up as thesis or semester projects.
ObjectiveThe objectives are (a) to understand the state-of-the-art in the field; (b) to learn to read, present and critique papers; (c) to engage in discussion and debate about research questions; and (d) to identify opportunities for new research.

Students are expected to attend the entire seminar, choose a topic for presentation from a given list, make a presentation on that topic, and lead the discussion. Further, for each reading, every student needs to submit a review before the in-class discussion. Students are evaluated on their submitted reviews, their presentation and discussion leadership, and participation in seminar discussions.
LiteratureA program will be posted here: Link, comprising of a list of papers the seminar group will cover.
Prerequisites / NoticeAn undergraduate-level understanding of networking, such that the student is familiar with concepts like reliable transport protocols (like TCP) and basics of Internet routing. ETH courses that fulfill this requirement: Computer Networks (252-0064-00L) and its predecessor (Operating Systems and Networks -- 252-0062-00L). Similar courses at other universities are also sufficient.
263-4505-00LAlgorithms for Large-Scale Graph Processing Information
The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
W2 credits2SM. Ghaffari
AbstractThis is a theory seminar, where we present and discuss recent algorithmic developments for
processing large-scale graphs. In particular, we focus on Massively Parallel Computation (MPC)
algorithms. MPC is a clean and general theoretical framework that captures the essential aspects
of computational problems in large-scale processing settings such as MapReduce, Hadoop,
Spark, Dryad, etc.
ObjectiveThis seminar familiarizes students with foundational aspects of large-scale graph processing,
and especially the related algorithmic tools and techniques. In particular, we discuss recent
developments in the area of Massively Parallel Computation. This is a mathematical abstraction
of practical large-scale processing settings such as MapReduce, and it has been receiving
significant attention over the past few years.

The seminar assumes no particular familiarity with parallel computation. However, we expect
that all the students are comfortable with basics of algorithms design and analysis, as well as
probability theory.

In the course of the seminar, the students learn how to structure a scientific presentation
(in English) which covers the key ideas of a paper, while omitting the less significant details.
ContentThe seminar will cover a number of the recent papers on Massively Parallel Computation.
As mentioned above, no familiarity with parallel computation is needed and all the relevant
background information will be explain by the instructor in the first lecture.
LiteratureThe papers will be presented in the first session of the seminar.
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