Search result: Catalogue data in Autumn Semester 2021

Doctoral Department of Computer Science Information
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Doctoral and Post-Doctoral Courses
NumberTitleTypeECTSHoursLecturers
» Course Catalogue of ETH Zurich
252-0945-13LDoctoral Seminar Machine Learning (HS21)
Only for Computer Science Ph.D. students.

This doctoral seminar is intended for PhD students affiliated with the Institute for Machine Learning. Other PhD students who work on machine learning projects or related topics need approval by at least one of the organizers to register for the seminar.
W2 credits1SJ. M. Buhmann, N. He, A. Krause, G. Rätsch, M. Sachan
AbstractAn essential aspect of any research project is dissemination of the findings arising from the study. Here we focus on oral communication, which includes: appropriate selection of material, preparation of the visual aids (slides and/or posters), and presentation skills.
ObjectiveThe seminar participants should learn how to prepare and deliver scientific talks as well as to deal with technical questions. Participants are also expected to actively contribute to discussions during presentations by others, thus learning and practicing critical thinking skills.
Prerequisites / NoticeThis doctoral seminar of the Machine Learning Laboratory of ETH is intended for PhD students who work on a machine learning project, i.e., for the PhD students of the ML lab.
252-1425-00LGeometry: Combinatorics and Algorithms Information W8 credits3V + 2U + 2AB. Gärtner, E. Welzl, M. Hoffmann, M. Wettstein
AbstractGeometric structures are useful in many areas, and there is a need to understand their structural properties, and to work with them algorithmically. The lecture addresses theoretical foundations concerning geometric structures. Central objects of interest are triangulations. We study combinatorial (Does a certain object exist?) and algorithmic questions (Can we find a certain object efficiently?)
ObjectiveThe goal is to make students familiar with fundamental concepts, techniques and results in combinatorial and computational geometry, so as to enable them to model, analyze, and solve theoretical and practical problems in the area and in various application domains.
In particular, we want to prepare students for conducting independent research, for instance, within the scope of a thesis project.
ContentPlanar and geometric graphs, embeddings and their representation (Whitney's Theorem, canonical orderings, DCEL), polygon triangulations and the art gallery theorem, convexity in R^d, planar convex hull algorithms (Jarvis Wrap, Graham Scan, Chan's Algorithm), point set triangulations, Delaunay triangulations (Lawson flips, lifting map, randomized incremental construction), Voronoi diagrams, the Crossing Lemma and incidence bounds, line arrangements (duality, Zone Theorem, ham-sandwich cuts), 3-SUM hardness, counting planar triangulations.
Lecture notesyes
LiteratureMark de Berg, Marc van Kreveld, Mark Overmars, Otfried Cheong, Computational Geometry: Algorithms and Applications, Springer, 3rd ed., 2008.
Satyan Devadoss, Joseph O'Rourke, Discrete and Computational Geometry, Princeton University Press, 2011.
Stefan Felsner, Geometric Graphs and Arrangements: Some Chapters from Combinatorial Geometry, Teubner, 2004.
Jiri Matousek, Lectures on Discrete Geometry, Springer, 2002.
Takao Nishizeki, Md. Saidur Rahman, Planar Graph Drawing, World Scientific, 2004.
Prerequisites / NoticePrerequisites: The course assumes basic knowledge of discrete mathematics and algorithms, as supplied in the first semesters of Bachelor Studies at ETH.
Outlook: In the following spring semester there is a seminar "Geometry: Combinatorics and Algorithms" that builds on this course. There are ample possibilities for Semester-, Bachelor- and Master Thesis projects in the area.
252-4202-00LSeminar in Theoretical Computer Science Information Restricted registration - show details W2 credits2SE. Welzl, B. Gärtner, M. Ghaffari, M. Hoffmann, J. Lengler, A. Steger, D. Steurer, 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.
Prerequisites / NoticeThis seminar takes place as part of the joint research seminar of several theory groups. Intended participation is for students with excellent performance only. Formal restriction is: prior successful participation in a master level seminar in theoretical computer science.
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 credits2SP. Müller, M. Püschel
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.
263-5255-10LFoundations of Reinforcement Learning (Only Assignments)
Only for Ph.D. students! Last cancellation/deregistration date for this graded semester performance: Thursday, 28 October 2021! Please note that after that date no deregistration will be accepted and the course will be considered as "fail".
W2 credits4AN. He
Abstract
Objective
ContentThis course focuses on theoretical and algorithmic foundations of reinforcement learning, through the lens of optimization, modern approximation, and learning theory. The course targets students with strong research interests in reinforcement learning, optimization under uncertainty, and data-driven control.
264-5800-18LDoctoral Seminar in Visual Computing (HS21) Information W1 credit1SM. Pollefeys, O. Sorkine Hornung, S. Tang
AbstractIn this doctoral seminar, current research at the Institute for Visual Computing will be presented and discussed. The goal is to learn about current research projects at our institute, to strengthen our expertise in the field, to provide a platform where research challenges caThis graduate seminar provides doctoral students in computer science a chance to read and discuss current research papers.
ObjectiveIn this doctoral seminar, current research at the Institute for Visual Computing will be presented and discussed. The goal is to learn about current research projects at our institute, to strengthen our expertise in the field, to provide a platform where research challenges can be discussed, and also to practice scientific presentations.
ContentCurrent research at the IVC will be presented and discussed.
Prerequisites / NoticeThis course requires solid knowledge in the area of Computer Graphics and Computer Vision as well as state-of-the-art research.
264-5812-00LWriting for Publication in Computer Science (WPCS) Restricted registration - show details
Number of participants limited to 15.

Only for D-INFK doctoral students.
Z2 credits1GS. Milligan
AbstractThis short course is designed to help junior researchers in Computer Science develop the skills needed to write their first research articles.
ObjectiveWriting for Publication in Computer Science is a short course (5 x 4-lesson workshops) designed to help doctoral students develop the skills needed to write their first research articles. The course deals with topics such as:
- understanding the needs of different target readerships,
- managing the writing process efficiently,
- structuring texts effectively,
- producing logical flow in sentences and paragraphs,
- editing texts before submission, and
- revising texts in response to colleagues' feedback and reviewers' comments.
ContentParticipants will be expected to produce a number of short texts (e.g., draft of a conference abstract) as homework assignments; they will receive individual feedback on these texts during the course. Wherever feasible, elements of participants' future conference/journal articles can be developed as assignments within the course, so it is likely to be particularly useful for those who have i) their data and are about to begin the writing process, or ii) an MSc thesis they would like to convert for publication.
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