UA Ruhr VVZ-Suche

Lehrstuhl für Datenverarbeitungssysteme
[080385] Scheduling Problems and Solutions — Vorlesung
Dr.-Ing. Uwe Schwiegelshohn, Sabine Winterhoff, M.Sc. Ganesh Nileshwar

Score: 13.93 Scheduling is generally understood as the mapping of jobs or tasks to machines or resources. In practice, these problems occur in various forms in the areas of industrial production, logistics, process management as well as in the generation of service schedules and timetables. In the context of this lecture we will first consider problems for the one machine model and analyze them by theoretical methods. Afterwards, we will use these results to address more complex problems with several machines. The third part of the lecture concerns different variants of production line problems. In the lecture we discuss deterministic and online algorithms. We distinguish so called easy and hard problems. The latter will although be addressed with heuristic approaches yielding performance guarantees

Informatik
[041243] Machine Learning Paradigms for Complex Data — Vorlesung
Erich Schubert, Emmanuel Müller, Daniel Gunter Wilmes

Score: 13.63 The lecture provides insights into advanced machine learning methods that form the basis for an emerging research area. Traditional methods have been considered for several years in the literature and are covered by basic machine learning lectures. However, due to the large and complex data used in today’s applications, some of these traditional methods are applicable only on relatively small and simple problem instances. Recently, research has addressed this challenge by proposing novel machine learning paradigms for large and high dimensional data. They aim at scalability with respect to size and dimensionality of data in todays and future applications. The lecture will derive novel challenges for machine learning out of recent application scenarios. The focus will be on advanced machine on the data. Outlier mining techniques in high dimensional data. Challenges and recent solutions in research and industrial projects. Overview on our future work in this research area. At the end of the lecture, the participants should be aware of – and able to explain – the necessity of advanced machine learning concepts. They should be able to assess and compare different approaches of data analysis Machine Learning Paradigms for Complex Data application demands. Overview of traditional machine learning techniques and their drawbacks. Abstract challenges due to high dimensional data. Novel machine learning paradigms in projections of high dimensional data. Novel solutions aiming at elimination of redundancy in data analytics results. Quality improvement by optimization techniques. Knowledge extraction by alternative views and projections

Institut für Diversitätsstudien
[152229] Bilingual first language acquisition — Seminar
Seyedehmaryam Fatemi

Score: 8.26 The prerequisite of this class is to prepare and study the uploaded material in moodle before each session. Eve V. Clark: First language acquisition, 2003 Annick De Houwer: Bilingual first language acquisition, 2009 Ellen Bialystok : Second-Language Acquisition and Bilingualism at an Early Age and the Impact on Early Cognitive Development, 2006 Stephanie DeAnda, Pascal Zesiger, Diane Poulin

Statistik
[050627] Generalized Linear Models — Vorlesung
Andreas Groll

Score: 8.13 The lecture will be given in an inverted classroom-style. Every week, 2 lecture videos will be uploaded in Moodle and each Thursday, from 10-11 am, there will be a Q&A session on those videos in lecture room CT/ZE 15 (BCI-Building in front of HG II). Start: Thursday, 07.04.2022, exceptionally from 11-12 am !!!

Lehrstuhl Informatik IX, Informatik
[041409] Uncertainty quantification in machine learning — Seminar
Emmanuel Müller, Bin Li, Simon Klüttermann

Score: 7.99 Uncertainty quantification in machine learning Seminar: Uncertainty quantification in machine learning We live in a world where we try to replace more and more tasks using computers and machines. However, there is barely any understanding of these models created using machine learning, and particular difficulty in understanding their reliability and measures of uncertainty. How do we really know whether a classifier performs well in real

Lehrstuhl Informatik IX, Informatik
[041408] Machine Learning Research — Seminar
Markus Pauly, Emmanuel Müller

Score: 7.98 Machine Learning Research

Lehrstuhl Informatik IX, Informatik
[040603] Interpretable Machine Learning — Proseminar
Emmanuel Müller, Simon Klüttermann

Score: 7.98 Interpretable Machine Learning

Lehrstuhl Informatik VIII, Informatik
[042638] Übung zu Unsupervised Machine Learning — Übung
Erich Schubert

Score: 7.98 Übung zu Unsupervised Machine Learning

Informatik
[041244] Übung zu Machine Learning Paradigms for Complex Data — Übung
Simon Klüttermann, Daniel Gunter Wilmes

Score: 7.79 Übung zu Machine Learning Paradigms for Complex Data

Physik
[020249] Maschinelles Lernen für Physiker*innen / Machine Learning for Physicists — Seminar
Olaf Nackenhorst, Florian Mentzel

Score: 7.61 Maschinelles Lernen für Physiker*innen / Machine Learning for Physicists

Maschinenbau
[072063] Machining Technology 2 (MMT) — Vorlesung mit Übung
Univ.-Prof. Dr.-Ing. Dirk Biermann, R. Tilger

Score: 7.61 Machining Technology 2 (MMT)

Physik
[020129] Quantum theory of semiconductors — Vorlesung
Doris Reiter

Score: 7.53 Semiconductors play a vital role in modern devices used in computers, smartphones and quantum technologies. Using a microscopic description of semiconductors, the lecture will introduce the basic concepts of semiconductor theory. The lecture covers several topics from semiconductor physics including semiconductor band structures, heterostructures, excitons, light-matter interaction, transport theory as well as two dimensional materials like graphene or transition metal dichalcogenides. This gives a solid background to understand modern research papers. Literature: A script will be provided during the lecture.

Lehrstuhl Informatik XII, Informatik
[042503] Computer Vision — Vorlesung
Univ.-Prof. Dr. Gernot Fink

Score: 7.27 Topical focus areas (Schwerpunktgebiete): 2 (..., Embedded Systems, ...), 7 (Intelligent Systems) Specialization Module (Vertiefungsmodul INF-MA-502) for Master (Applied) Computer Science For up-to-date information on the lecture please refer to the accompanying web page. NOTE: There is no Moodle room associated with this lecture!

Physik
[020128] Ask me anything: Quantum Dots — Seminar
Doris Reiter

Score: 7.27 To cover these topics, the students are given material (either lecture notes, fundamental papers or recent research articles) covering one session. Each session will be hosted by a student, who is responsible for asking questions to the lecturer, such that the full content of the session is covered. The chair shall also involve other students to participate in the discussions.

Elektrotechnik und Informationstechnik, Bio- und Chemieingenieurwesen
[061802] PAS - Machine Learning Methods for Engineers — Übung
Prof. Dr. Sergio Lucia Gil, M.Sc. Felix Malte Hermes Fiedler

Score: 7.03 PAS - Machine Learning Methods for Engineers

Process Automation Systems, Bio- und Chemieingenieurwesen
[061801] PAS - Machine Learning Methods for Engineers — Vorlesung
Prof. Dr. Sergio Lucia Gil, M.Sc. Felix Malte Hermes Fiedler, Vanessa Wojcik

Score: 6.89 PAS - Machine Learning Methods for Engineers

Institut für katholische Theologie
[147128] Vorlesung Systematische Theologie: Soteriologie - Lehre von der Erlösung / Lecture on Systematic Theology: Doctrine of Redemption — Vorlesung
Gregor Taxacher

Score: 6.57 Vorlesung Systematische Theologie: Soteriologie - Lehre von der Erlösung / Lecture on Systematic Theology: Doctrine of Redemption

Lehrstuhl Informatik VIII, Informatik
[042637] Unsupervised Machine Learning (canceled) — Vorlesung
Erich Schubert

Score: 6.54 Unsupervised Machine Learning (canceled)

Institut für katholische Theologie
[147129] Didaktisches Seminar zur Vorlesung Soteriologie / Didactic Seminar on the Lecture Soteriologie — Seminar
Gregor Taxacher

Score: 6.36 Didaktisches Seminar zur Vorlesung Soteriologie / Didactic Seminar on the Lecture Soteriologie

Physik
[020505] Practical aspects of instrumentation — Vorlesung mit Übung
Dozenten der Elementarteilchenphysik, Kevin Alexander Kröninger

Score: 5.99 The lecture will be given by Prof. Dr. Andreas Jung from Purdue University who will hold the Ulrich Bonse visiting chair for instrumentation during the summer term 2022.

Lehrstuhl Mathematische Statistik und industrielle Anwendungen, Statistik
[059876] Introduction to Causal Inference — Vorlesung mit Übung
Markus Pauly, M.Sc. Philip Buczak, Menggang Yu

Score: 4.74 Please see https://www.statistik.tu-dortmund.de/3099.html for more information. Note: The course will run from June, 17th to July, 29th. As an exception, the first lecture will take place during the tutorial slot on June, 17th from 14:15 - 15:45 in CDI 120.

Raumplanung, Fachgebiet International Planning Studies
[092012a] Lecture Series International Planning Sessions — Seminar
Ing. Sophie Schramm

Score: 4.47 Lecture Series International Planning Sessions

Lehrstuhl Informatik II, Informatik, Lehrstuhl Informatik I
[040145] Theoretische Informatik für Studierende der Angewandten Informatik — Vorlesung
N. N

Score: 4.11 Anmeldung im Sommersemester 2022 Bitte melden Sie sich zur Vorlesung "Grundbegriffe der Theoretischen Informatik" an. https://www.lsf.tu-dortmund.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&veranstaltung.veranstid=266609&purge=y&topitem=lectures⊂item=editlecture&asi=t0I2cUuJt6uNrBAJJwGo

Physik
[020242] Schwerpunktspraktikum ´Teilchenphysik und Detektoren´ / Advanced Laboratory course: Particle physics — Praktikum
Dr. Wolfgang Rhode, Johannes Albrecht, Kevin Alexander Kröninger, Dirk Wiedner

Score: 3.75 Content: Experimental techniques in particle physics including detector physics (semiconductor and scintillating fiber detectors), data analysis (CP violation and top-quark physics, reconstruction of particles) and advanced statistical methods (machine learning). Learning outcome: The students will obtain basic knowledge about particle and medical physics detectors, the technology used

Physik
[020636] Introduction to particle accelerator physics — Seminar
Adolfo Vélez Saiz

Score: 3.62 I will try as much as possible to accomodate the lectures not to coincide with your other duties. How: The 1st week will be devoted to go through the material you will be provided with. You can download the lectures (ppt) from the moodle and we will dedicate the time to go deeper into the introduced concepts. In 2nd week you will be given the choice to select a topic on which you will have to do

Arbeitsgebiet Datentechnik
[000000] Versuch 207 (Digitaler Signalprozessor/Digital Signal Processor) — Labor
Carolin-Maria Linker

Score: 2.99 Stunden ablaufen. Für diese Session werden verschiedene Termine angeboten. Die Termine werden auf deutsch und englisch angeboten; die Wahl der Sprache ist frei. English - The practical training lab "Digital Signal Processor" is a mandatory part of the lectures "Signal Processing for Robotics and Automation (SPRA)" and "Theoretische Grundlagen der Informationstechnik (TGIT)". The material provided

Statistik
[051096] Visualisierung von Sportdaten — Seminar
Katja Ickstadt, Philipp Doebler, Andreas Groll, Dipl.-Journ. Christina Elmer

Score: 2.99 registration in the LSF is not necessary. All interested students will be informed by the lecturers whether they have received a place or not.

Lehrstuhl Bodenpolitik, Bodenmanagement und kommunales Vermessungswesen, Raumplanung
[0920384] Land Policies in Europe — Seminar
Dipl.-Ing. Thomas Hartmann, M.Sc. Peter Rico Davids

Score: 1.93 will present each other the results of their study. • Second, students learn how to systematically analyse land policies and its instruments. Students will learn how policy instruments impact scarcity of land, based on effectiveness, efficiency, legitimacy, and justice. This teaching goals will be taught with a series of input lectures and with the book “Planning, Law and Economics: the rules we make

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28 VVZ Einträge (aus 23360) gefunden für: Lecture Machines Diane Lucio