Search result: Catalogue data in Autumn Semester 2016

Number	Title	Type	ECTS	Hours	Lecturers
Computer Science Master
Focus Courses
Focus Courses in Information Systems
Seminar Information Systems
263-3504-00L	Hardware Acceleration for Data Processing	W	2 credits	2S	G. Alonso, T. Hoefler, O. Mutlu
Abstract	The seminar will cover topics related to data processing using new hardware in general and hardware accelerators (GPU, FPGA, specialized processors) in particular.
Learning objective	The seminar will cover topics related to data processing using new hardware in general and hardware accelerators (GPU, FPGA, specialized processors) in particular.
Content	The 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 / Notice	Students taking this seminar should have the necessary background in systems and low level programming.
252-5051-00L	Advanced Topics in Machine Learning	W	2 credits	2S	J. M. Buhmann, T. Hofmann, A. Krause, G. Rätsch
Abstract	In 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.
Learning objective	The 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.
Content	The 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.
Literature	The papers will be presented in the first session of the seminar.
252-3001-00L	Advanced Topics in Information Systems Does not take place this semester. Number of participants limited to 16.	W	2 credits	2S	M. Norrie
Abstract	This seminar course will discuss research topics in the area of information systems. We will read recent research papers on a selected topic, and present/discuss them in class.
Learning objective	The goal is to introduce students to current research, and to enable them to read, understand, and present scientific papers.
Content	Each participant will be required to give a presentation of about 30 mins followed by a discussion on an assigned topic. In addition, each participant will be assigned as a buddy on another paper which means that they must read the paper and be prepared to start of the discussion on the paper with some comments and questions. Students also have to submit a 2-page summary of the paper that they present. Grading will depend on the quality of the talk, the report, and also active participation during the seminar.

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