September 2020 - informatik-vortraege

Einladung Informatik-Oberseminar Malte Nuhn
by Sekretariat I6 30 May '22

30 May '22

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Freitag, 12. Juli 2019, 10.00 Uhr Ort: Informatikzentrum, E3, Raum 9222 Referent: Dipl.-Inform. Malte Nuhn Thema: Unsupervised Training with Applications in Natural Language Processing// Abstract: The state-of-the-art algorithms for various natural language processing tasks require large amounts of labeled training data. At the same time, obtaining labeled data of high quality is often the most costly step in setting up natural language processing systems.Opposed to this, unlabeled data is much cheaper to obtain and available in larger amounts.Currently, only few training algorithms make use of unlabeled data. In practice, training with only unlabeled data is not performed at all. In this thesis, we study how unlabeled data can be used to train a variety of models used in natural language processing. In particular, we study models applicable to solving substitution ciphers, spelling correction, and machine translation. This thesis lays the groundwork for unsupervised training by presenting and analyzing the corresponding models and unsupervised training problems in a consistent manner.We show that the unsupervised training problem that occurs when breaking one-to-one substitution ciphers is equivalent to the quadratic assignment problem (QAP) if a bigram language model is incorporated and therefore NP-hard. Based on this analysis, we present an effective algorithm for unsupervised training for deterministic substitutions. In the case of English one-to-one substitution ciphers, we show that our novel algorithm achieves results close to human performance, as presented in [Shannon 49]. Also, with this algorithm, we present, to the best of our knowledge, the first automatic decipherment of the second part of the Beale ciphers.Further, for the task of spelling correction, we work out the details of the EM algorithm [Dempster & Laird + 77] and experimentally show that the error rates achieved using purely unsupervised training reach those of supervised training.For handling large vocabularies, we introduce a novel model initialization as well as multiple training procedures that significantly speed up training without hurting the performance of the resulting models significantly.By incorporating an alignment model, we further extend this model such that it can be applied to the task of machine translation. We show that the true lexical and alignment model parameters can be learned without any labeled data: We experimentally show that the corresponding likelihood function attains its maximum for the true model parameters if a sufficient amount of unlabeled data is available. Further, for the problem of spelling correction with symbol substitutions and local swaps, we also show experimentally that the performance achieved with purely unsupervised EM training reaches that of supervised training. Finally, using the methods developed in this thesis, we present results on an unsupervised training task for machine translation with a ten times larger vocabulary than that of tasks investigated in previous work. Es laden ein: die Dozentinnen und Dozenten der Informatik _______________________________________________ -- -- Stephanie Jansen Faculty of Mathematics, Computer Science and Natural Sciences HLTPR - Human Language Technology and Pattern Recognition RWTH Aachen University Ahornstraße 55 D-52074 Aachen Tel. Frau Jansen: +49 241 80-216 06 Tel. Frau Andersen: +49 241 80-216 01 Fax: +49 241 80-22219 sek(a)i6.informatik.rwth-aachen.de www.hltpr.rwth-aachen.de Tel: +49 241 80-216 01/06 Fax: +49 241 80-22219 sek(a)i6.informatik.rwth-aachen.de www.hltpr.rwth-aachen.de

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Einladung Informatik-Oberseminar Dr. Andreas Wortmann, 03. November 2020, 12:30 Uhr
by Bernhard Rumpe 29 Sep '20

29 Sep '20

********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * *********************************************************************** Zeit: Dienstag, 03. November 2020, 12:30 Uhr Zoom: https://rwth.zoom.us/j/92659511051?pwd=TmVibnlCNUdYZzlZSW52eCs0V2RjQT09 Referent: Dr. Andreas Wortmann Thema: Model-Driven Architecture and Behavior of Cyber-Physical Systems Vorstellung des Habilitationsvorhabens. Abstract: Systems engineering has produced striking results in many domains. Researchers and practitioners have devised concepts, methods, tools that autonomously move vehicles, enable doctors to conduct remote surgeries across continents, and sent astronauts into space. All of these cyber-physical systems are driven by software whose complexity increases tremendously. Overcompensating this growth in software and systems complexity demands novel methods that increase the abstraction in systems engineering, advance automation, and facilitate the integration of domain expert solutions. Model-based systems engineering aims to address this complexity by advancing systems engineering from its contemporary document-based processes to sophisticated model-based processes. In the latter, abstract models serve as means for systems design, communication, documentation, and basis for implementation. But to overcompensate the growth in complexity, using models as secondary artifacts is insufficient. Comprehensive research in software engineering has led to recognizing that model-driven processes, in which models are the primary engineering artifacts, can significantly improve abstraction, automation, and domain-specific modeling to address the increasing complexity in systems engineering. Yet, model-based systems engineering focuses on informal models that are hardly accessible to meaningful automation and overly generic. This thesis summarizes 14 selected publications of a research program towards a model-driven systems engineering that operates on domain-specific modeling languages, supports sophisticated modeling methods, and enables the systematic operation of cyber-physical systems. The results of this research program cover four substantial challenges towards the model-driven engineering of cyber-physical systems: First, it contributes to understanding the use of models and modeling languages for cyber-physical systems through two comprehensive literature studies on modeling for cyber-physical systems in Industry 4.0 and mobile robotics. The studies surveyed over 3.000 publications each and produced insights into requirements for the efficient model-driven engineering and operations of cyber-physical systems in both domains. Second, it conduces novel foundations for the efficient engineering of domain-specific modeling languages based on the requirements identified in both studies. These foundations introduce innovative notions of language components and their composition upon which families of domain-specific modeling languages can be created systematically efficiently. Third, it leverages these foundations to produce modeling languages to describe functional architectures and geometric-physical architectures of cyber-physical systems that support unprecedented automated modeling methods, including tracing, decomposition, and semantic differencing, to facilitate modeling, maintaining, and evolving these architectures. Fourth, it exploits the novel language engineering foundations and the unprecedented automated modeling methods to alleviate the systematic operation of cyber-physical systems with digital twins that represent and optimize the observed systems. Hence, this research program forges a bridge from observations on modeling cyber-physical systems, over software language engineering and modeling methods, to their operation that supports researchers and practitioners to advance from the contemporary document-based engineering of cyber-physical systems to their systematic model-driven engineering. Vita: Andreas Wortmann is a tenured research associate at the Chair for Software Engineering at RWTH Aachen University. There, he leads a team on model-driven systems engineering, coordinates a workstream of the Internet of Production excellence cluster, and advises the Center for Systems Engineering. He conducts research in model-driven software and systems engineering, formal methods in software engineering, and software language engineering, which is documented in over 70 publications. Moreover, he has chaired and organized various international conferences and workshops, serves on the board of the European Association for Programming Languages and Systems (EAPLS), and co-chairs the working group on model-based systems engineering of the German INCOSE chapter GfSE. Es laden ein: die Dozentinnen und Dozenten der Informatik -- ---------------------------------------------------------------- Prof. Dr. Bernhard Rumpe | http://www.se-rwth.de Lehrstuhl Software Engineering | Informatik 3 Ahornstr. 55, 52074 Aachen, Germany | RWTH Aachen University Phone ++49 241 80-21301 / Fax -22218 |

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Einladung: Informatik Oberseminar Markus Hoehnerbach
by Markus Hoehnerbach 15 Sep '20

15 Sep '20

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Dienstag, 22. September 2020, 16.00 Uhr Ort: Videokonferenz (Zoom-Meeting, Informationen siehe unten) Referent: Markus Hoehnerbach M.Sc. High-Performance and Automatic Computing Thema: A Framework for the Vectorization of Molecular Dynamics Kernels Abstract: We introduce a domain-specific language (DSL) for many-body potentials, which are used in molecular dynamics (MD) simulations in the area of materials science. We also introduce a compiler to translate the DSL into high-performance code suitable for modern supercomputers. We begin by studying ways to speedup up potentials on supercomputers using two case studies: The Tersoff and the AIREBO potentials. In both case studies, we identify a number of optimizations, both domain-specific and general, to achieve speedups of up to 5x; we also introduce a method to keep the resulting code performance portable. During the AIREBO case study, we also discover that the existing code contains a number of errors. This experience motivates us to include the derivation step, the most error-prone step in manual optimization, in our automation effort. After having identified beneficial optimization techniques, we create a ``potential compiler'', short PotC, which generates fully-usable performance-portable potential implementations from specifications written in our DSL. DSL code is significantly shorter (20x to 30x) than a manual code, reducing both manual work and opportunities to introduce bugs. We present performance results on five different platforms: Three CPU platforms (Broadwell, Knights Landing, and Skylake) and two GPU platforms (Pascal and Volta). While the performance in some cases remains far below that of hand-written code, it also manages to match or exceed manually written implementations in other cases. For these cases, we achieve speedups of up to 9x compared to non-vectorized code. Es laden ein: die Dozentinnen und Dozenten der Informatik ******************************** Thema: Dissertation M. Höhnerbach Uhrzeit: 22.Sep.2020 03:45 PM Paris Zoom-Meeting beitreten https://rwth.zoom.us/j/98920238040?pwd=Q3F1OStEcklpcDV1Vk5IWEp0cFFEQT09 Meeting-ID: 989 2023 8040 Kenncode: 668020

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