Suchergebnis: Katalogdaten im Frühjahrssemester 2018

Informatik Master Information
Vertiefungsfächer
Vertiefung General Studies
Seminar in General Studies
NummerTitelTypECTSUmfangDozierende
252-3002-00LAlgorithms for Database Systems Information
Limited number of participants.
W2 KP2SP. Widmayer, P. Uznanski
KurzbeschreibungQuery processing, optimization, stream-based systems, distributed and parallel databases, non-standard databases.
LernzielDevelop an understanding of selected problems of current interest in the area of algorithms for database systems.
252-3100-00LComputer Supported Cooperative Work Information Belegung eingeschränkt - Details anzeigen
Maximale Teilnehmerzahl: 12

Findet zum letzten Mal statt.
W2 KP2SM. Norrie
KurzbeschreibungIm Forschungsbereich "computerunterstütztes kooperatives Arbeiten" (CSCW) steht die Zusammenarbeit von Benutzern mittels EDV-Technologie im Mittelpunkt des Interesses. Es handelt sich dabei um multidisziplinäre Forschung welche soziale, theoretische, praktische und technische Aspekte von Zusammenarbeit mit einschliesst.
LernzielComputer-Supported Cooperative Work (CSCW) is the study of how people work together using computer technology. It is a multi-disciplinary research field dealing with the social, theoretical, practical and technical aspects of collaboration and how the use of technology can affect groups, organisations, communities and societies. The CSCW community is interested in how people use everyday tools such as email, the web and chat systems as well as specialist groupware applications that support groups of people engaged in shared tasks such as software development or product design. A better understanding of how people communicate and work together can in turn lead to a better understanding of the problems of current technologies and systems and influence the design of new technologies and tools.
252-3600-02LSmart Systems Seminar Information W2 KP2SO. Hilliges, S. Coros, F. Mattern
KurzbeschreibungSeminar zu unterschiedlichen Themen aus den Bereichen Ubiquitous Computing, Mensch-Maschine-Kommunikation, Robotik und Computer Grafik und verwandter Gebiete.
LernzielErwerb von Kenntnissen zu unterschiedlichen aktuellen Themen aus den Bereichen Ubiquitous Computing, Mensch-Maschine Interaktion, Robotik, 3D Druck und Computer Grafik
252-4102-00LSeminar on Randomized Algorithms and Probabilistic MethodsW2 KP2SA. Steger
KurzbeschreibungThe aim of the seminar is to study papers which bring the students to the forefront of today's research topics. This semester we will study selected papers of the conference Symposium on Discrete Algorithms (SODA18).
LernzielRead papers from the forefront of today's research; learn how to give a scientific talk.
Voraussetzungen / BesonderesThe seminar is open for both students from mathematics and students from computer science. As prerequisite we require that you passed the course Randomized Algorithms and Probabilistic Methods (or equivalent, if you come from abroad).
252-4202-00LSeminar in Theoretical Computer Science Information W2 KP2SE. Welzl, B. Gärtner, M. Hoffmann, J. Lengler, A. Steger, B. Sudakov
KurzbeschreibungPresentation of recent publications in theoretical computer science, including results by diploma, masters and doctoral candidates.
LernzielTo get an overview of current research in the areas covered by the involved research groups. To present results from the literature.
263-4203-00LGeometry: Combinatorics and Algorithms Information W2 KP2SM. Hoffmann, E. Welzl, L. F. Barba Flores, P. Valtr
KurzbeschreibungThis seminar complements the course Geometry: Combinatorics & Algorithms. Students of the seminar will present original research papers, some classic and some of them very recent.
LernzielEach student is expected to read, understand, and elaborate on a selected research paper. To this end, (s)he should give a 45-min. presentation about the paper. The process includes

* getting an overview of the related literature;
* understanding and working out the background/motivation:
why and where are the questions addressed relevant?
* understanding the contents of the paper in all details;
* selecting parts suitable for the presentation;
* presenting the selected parts in such a way that an audience
with some basic background in geometry and graph theory can easily understand and appreciate it.
InhaltThis seminar is held once a year and complements the course Geometry: Combinatorics & Algorithms. Students of the seminar will present original research papers, some classic and some of them very recent. The seminar is a good preparation for a master, diploma, or semester thesis in the area.
Voraussetzungen / BesonderesPrerequisite: Successful participation in the course "Geometry: Combinatorics & Algorithms" (takes place every HS) is required.
252-4302-00LSeminar Algorithmic Game Theory Information
Limited number of participants.
W2 KP2SP. Widmayer, P. Penna
KurzbeschreibungIn the seminar we will get familiar with the current original research in the area of algorithmic game theory by reading and presenting selected research papers in that area.
LernzielDevelop an understanding of selected problems of current interest in the area of algorithmic game theory, and a practice of a scientific presentation.
InhaltStudy and understanding of selected topics of current interest in algorithmic game theory such as: Complexity Results (class PPAD, PLS, NP), Sponsored Search, Approximation Algorithms via Algorithmic Game Theory, Price of Anarchy, New paradigms of computation (e.g., envy-fee, truthful), Mechanism Design.
LiteraturSelected research articles.
Voraussetzungen / BesonderesYou must have passed our "Algorithmic Game Theory" class (or have acquired equivalent knowledge, in exceptional cases).
252-4800-00LInformation & Physics Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 120.
Previously called Quantum Information and Cryptography

Um das vorhandene Angebot optimal auszunutzen, behält sich das D-INFK vor, Belegungen von Studierenden zu löschen, die sich in mehreren Veranstaltungen dieser Kategorie eingeschrieben haben, bereits die erforderlichen Leistungen in dieser Kategorie erbracht haben oder aus anderen organisatorischen Gründen nicht auf die Belegung der Veranstaltung angewiesen sind.
W2 KP4SS. Wolf
KurzbeschreibungEs werden verschiedene Themen im Grenzgebiet der Bereiche Quantenphysik, Informationstheorie und Kryptographie behandelt.
LernzielThemen im Grenzgebiet der Bereiche Quantenphysik, Informationstheorie und Kryptographie werden behandelt.
252-5251-00LComputational Science
Takes place for the last time.
W2 KP2SP. Arbenz, P. Chatzidoukas
KurzbeschreibungSeminarteilnehmer studieren grundlegende Papiere aus der Computational Science und halten in einem 40-min. Vortrag (auf Englisch). Der Vortrag (Struktur, Inhalt, Darstellung) ist mit dem verantw. Professor vorzubesprechen. Der Vortrag muss so gehalten werden, dass ihn die anderen Seminarteilnehmer verstehen und etwas lernen können. Teilnahme während des ganzen Semesters ist
vorgeschrieben.
LernzielStudieren und präsentieren einer grundlegenden Arbeit aus dem Bereich der Computational Science. Lernen, über ein wissenschaftliches Thema vorzutragen.
InhaltTeilnehmer am Seminar studieren grundlegende Papiere aus dem Bereich Computational Science und tragen darüber (auf Englisch) in einem 40-minütigen Vortrag vor. Vor der Präsentation soll der Vortrag (bzgl. Struktur, Inhalt, Darstellung) mit dem verantwortlichen Professor besprochen werden. Der Vortrag muss in einer Weise gegeben werden, dass ihn die anderen Seminarteilnehmer verstehen können und etwas lernen können. Teilnahme während des ganzen Semesters ist vorgeschrieben.
Skriptkeines
LiteraturPapiere werden in der ersten Semesterwoche verteilt.
252-5704-00LAdvanced Methods in Computer Graphics Information Belegung eingeschränkt - Details anzeigen
Maximale Teilnehmerzahl: 24
W2 KP2SM. Gross
KurzbeschreibungThis seminar covers advanced topics in computer graphics with a focus on the latest research results. Topics include modeling, rendering, visualization,
animation, physical simulation, computational photography, and others.
LernzielThe goal is to obtain an in-depth understanding of actual problems and
research topics in the field of computer graphics as well as improve
presentation and critical analysis skills.
263-2100-00LResearch Topics in Software Engineering Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 22.
W2 KP2ST. Gross
KurzbeschreibungThis seminar introduces students to the latest research trends that help to improve various aspects of software quality.

Topics cover the following areas of research: Compilers, domain-specific languages, concurrency, formal methods, performance optimization, program analysis, program generation, program synthesis, testing, tools, verification
LernzielAt the end of the course, the students should be:

- familiar with a broad range of key research results in the area as well as their applications.

- know how to read and assess high quality research papers

- be able to highlight practical examples/applications, limitations of existing work, and outline potential improvements.
InhaltThe course will be structured as a sequence of presentations of high-quality research papers, spanning both theory and practice. These papers will have typically appeared in top conferences spanning several areas such as POPL, PLDI, OOPSLA, OSDI, ASPLOS, SOSP, AAAI, ICML and others.
LiteraturThe publications to be presented will be announced on the seminar home page at least one week before the first session.
Voraussetzungen / BesonderesPapers will be distributed during the first lecture.
263-2926-00LDeep Learning for Big Code Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 24.
W2 KP2SM. Vechev
KurzbeschreibungThe 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.
LernzielThe 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.
InhaltThe 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.
Voraussetzungen / BesonderesThe 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 Belegung eingeschränkt - Details anzeigen
Number of participants limited to 26.
W2 KP2SM. Vechev, D. Drachsler Cohen, P. Tsankov
KurzbeschreibungThis seminar introduces students to the latest research trends in the field of blockchains.
LernzielThe 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.
InhaltThis 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.
263-3830-00LSoftware Defined Networking: The Data Centre Perspective Information W2 KP2ST. Roscoe, D. Wagenknecht-Dimitrova
KurzbeschreibungSoftware Defined Networks (SDN) is a change supported not only by research but also industry and redifens how traditional network management and configuration is been done.
LernzielThrough review and discussion of literature on an exciting new trend in networking, the students get the opportunity to get familiar with one of the most promising new developments in data centre connectivity, while at the same time they can develop soft skills related to the evaluation and presentation of professional content.
InhaltSoftware Defined Networks (SDN) is a change supported not only by research but also industry and redifens how traditional network management and configuration is been done. Although much has been already investigated and there are already functional SDN-enabled switches there are many open questions ahead of the adoption of SDN inside and outside the data centre (traditional or cloud-based). With a series of seminars we will reflect on the challenges, adoption strategies and future trends of SDN to create an understanding how SDN is affecting the network operators' industry.
LiteraturThe seminar is based on recent publications by academia and industry. Links to the publications are placed on the Seminar page and can be downloaded from any location with access to the ETH campus network.
Voraussetzungen / BesonderesThe seminar bases on active and interactive participation of the students.
263-3840-00LHardware Architectures for Machine Learning Information W2 KP2SG. Alonso, T. Hoefler, O. Mutlu, C. Zhang
KurzbeschreibungThe seminar covers recent results in the increasingly important field of hardware acceleration for data science and machine learning, both in dedicated machines or in data centers.
LernzielThe seminar aims at students interested in the system aspects of machine learning, who are willing to bridge the gap across traditional disciplines: machine learning, databases, systems, and computer architecture.
InhaltThe seminar is intended to cover recent results in the increasingly important field of hardware acceleration for data science and machine learning, both in dedicated machines or in data centers.
Voraussetzungen / BesonderesThe seminar should be of special interest to students intending to complete a master's thesis or a doctoral dissertation in related topics.
263-4845-00LDistributed Stream Processing: Systems and Algorithms Information
Findet dieses Semester nicht statt.
W2 KP2S
KurzbeschreibungIn this seminar, we will study the design and architecture of modern distributed streaming systems as well as fundamental algorithms for analyzing data streams. We will also consider current research topics and open issues in the area of distributed stream processing.
LernzielThe seminar will focus on high-impact research contributions addressing open issues in the design and implementation of modern distributed stream processors. In particular, the students will read, review, present, and discuss a series of research and industrial papers.
InhaltModern distributed stream processing technology enables continuous, fast, and reliable analysis of large-scale unbounded datasets. Stream processing has recently become highly popular across industry and academia due to its capabilities to both improve established data processing tasks and to facilitate novel applications with real-time requirements.

The students will read, review, present, and discuss a series of research and industrial papers covering the following topics:

- Fault-tolerance and processing guarantees
- State management
- Windowing semantics and optimizations
- Basic data stream mining algorithms (e.g. sampling, counting, filtering)
- Query languages and libraries for stream processing (e.g. Complex Event Processing, online machine learning)
263-5904-00LDeep Learning for Computer Vision: Seminal Work Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 24.
W2 KP2ST. Sattler, L. M. Koch
KurzbeschreibungThis seminar covers seminal papers on the topic of deep learning for computer vision. The students will present and discuss the papers and gain an understanding of the most influential research in this area - both past and present.
LernzielThe objectives of this seminar are two-fold. Firstly, the aim is to provide a solid understanding of key contributions to the field of deep learning for vision (including a historical perspective as well as recent work). Secondly, the students will learn to critically read and analyse original research papers and judge their impact, as well as how to give a scientific presentation and lead a discussion on their topic.
InhaltThe seminar will start with introductory lectures to provide (1) a compact overview of challenges and relevant machine learning and deep learning research, and (2) a tutorial on critical analysis and presentation of research papers. Each student then chooses one paper from the provided collection to present during the remainder of the seminar. The students will be supported in the preparation of their presentation by the seminar assistants.
SkriptThe selection of research papers will be presented at the beginning of the semester.
LiteraturThe course "Machine Learning" is recommended.
227-0126-00LAdvanced Topics in Networked Embedded Systems Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 12.
W2 KP1SL. Thiele, J. Beutel, Z. Zhou
KurzbeschreibungThe seminar will cover advanced topics in networked embedded systems. A particular focus are cyber-physical systems and sensor networks in various application domains.
LernzielThe goal is to get a deeper understanding on leading edge technologies in the discipline, on classes of applications, and on current as well as future research directions.
InhaltThe seminar enables Master students, PhDs and Postdocs to learn about latest breakthroughs in wireless sensor networks, networked embedded systems and devices, and energy-harvesting in several application domains, including environmental monitoring, tracking, smart buildings and control. Participants are requested to actively participate in the organization and preparation of the seminar.
227-0559-00LSeminar in Distributed Computing Information W2 KP2SR. Wattenhofer
KurzbeschreibungIn this seminar participating students present and discuss recent research papers in the area of distributed computing. The seminar consists of algorithmic as well as systems papers in distributed computing theory, peer-to-peer computing, ad hoc and sensor networking, or multi-core computing.
LernzielIn the last two decades, we have experienced an unprecedented growth in the area of distributed systems and networks; distributed computing now encompasses many of the activities occurring in today's computer and communications world. This course introduces the basics of distributed computing, highlighting common themes and techniques. We study the fundamental issues underlying the design of distributed systems: communication, coordination, synchronization, uncertainty. We explore essential algorithmic ideas and lower bound techniques.

In this seminar, students present the latest work in this domain.

Seminar language: English
InhaltDifferent each year. For details see: Link
SkriptSlides of presentations will be made available.
LiteraturPapers.
The actual paper selection can be found on Link.
851-0740-00LBig Data, Law, and Policy Belegung eingeschränkt - Details anzeigen
Number of participants limited to 35

Students will be informed by 4.3.2018 at the latest
W3 KP2SS. Bechtold, T. Roscoe, E. Vayena
KurzbeschreibungThis course introduces students to societal perspectives on the big data revolution. Discussing important contributions from machine learning and data science, the course explores their legal, economic, ethical, and political implications in the past, present, and future.
LernzielThis course is intended both for students of machine learning and data science who want to reflect on the societal implications of their field, and for students from other disciplines who want to explore the societal impact of data sciences. The course will first discuss some of the methodological foundations of machine learning, followed by a discussion of research papers and real-world applications where big data and societal values may clash. Potential topics include the implications of big data for privacy, liability, insurance, health systems, voting, and democratic institutions, as well as the use of predictive algorithms for price discrimination and the criminal justice system. Guest speakers, weekly readings and reaction papers ensure a lively debate among participants from various backgrounds.
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