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1
ESE Kongress — Embedded Software Engineering Kongress
02 Dec 2024 - 05 Dec 2024 • Sindelfingen, Germany
Organizer:
MicroConsult Microelectronics Consulting & Training GmbH & Vogel Communications Group GmbH & Co. KG
Abstract:
Der ESE Kongress ist Deutschlands Leitkongress der Embedded-Softwarebranche. Jedes Jahr im Dezember treffen sich über 1.200 Professionals, um sich über aktuelle Technologien und Methoden zu informieren, Trends zu diskutieren sowie die Weichen für die Zukunft zu stellen. Der Embedded Software Engineering Kongress ist die einzige deutschsprachige Veranstaltung, die sich ausschließlich und tiefgehend den vielfältigen Themen und Herausforderungen bei der Entwicklung von Geräte- und Systemsoftware für Industrieanwendungen, Automotive-Elektronik, Kommunikation sowie Consumer- und Medizintechnik widmet.
Contact:
Email: s.pagler@microconsult.com
Topics:
Embedded-Software, Software-Entwicklung, Programmierung, Systems Engineering, Software Engineering, Weiterbildung, ESE Kongress, MicroConsult, Elektronikpraxis, Vogel Communications Group
Event listing ID:
1629715
Related subject(s):
Event website:
2
embedded world Conference 2025
11 Mar 2025 - 13 Mar 2025 • Nürnberg, Germany
Organizer:
WEKA FACHMEDIEN GMBH
Event listing ID:
1622031
Related subject(s):
3
Dagstuhl-Seminar — Learned Predictions for Data Structures and Running Time
27 Apr 2025 - 02 May 2025 • Schloss Dagstuhl – Wadern, Germany
Organizer:
Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH
Abstract:
A long-standing question in theoretical computer science is to offer analysis tools for improving performance on typical everyday, non-worst-case instances. A recent model addressing this goal is the algorithms-with-predictions model: each problem instance comes with a possibly error-prone prediction, and the worst-case running time is given as a function of the error in that prediction. This model reflects how recent advances in machine learning are able to make reasonably good predictions on practical ‒ even very complex ‒ datasets. The algorithms-with-predictions model has been used to give strong approximation-ratio guarantees for fundamental online algorithms like scheduling and caching. How to leverage predictions to speed up running time of offline algorithms and data structures has received less attention. This Dagstuhl Seminar aims to bring together researchers from the data structures, combinatorial optimization and learned predictions communities to address the challenges of adopting learned predictions for improving running time guarantees.
Event listing ID:
1626740
Related subject(s):


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Last updated: 19 July 2024