Suchergebnis: Katalogdaten im Frühjahrssemester 2018

Informatik Master Information
Vertiefungsfächer
Vertiefung in Distributed Systems
Seminar in Distributed Systems
NummerTitelTypECTSUmfangDozierende
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
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)
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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