informatik-vortraege Juli 2019

informatik-vortraege@lists.rwth-aachen.de

3 Teilnehmer
3 Diskussionen

Einladung Informatik-Oberseminar Malte Nuhn

von Sekretariat I6

+********************************************************************** * * * 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

1 Jahr, 10 Monate

Einladung Informatik Oberseminar Sebastian Pick

von Sebastian Pick

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Montag, 15. Juli 2019, 16.00 Uhr Ort: Seminarraum 001, IT Center, Kopernikusstr. 6 Referent: Dipl.-Inform. Sebastian Pick Thema: Interactive Data Annotation for Virtual Reality Applications Abstract: Virtual Reality (VR) offers the unique possibility to explore data sets in a highly immersive and interactive fashion. A key aspect of this exploration process is the acquisition of insights and findings concerning the involved data. In this context, it becomes the task of so-called annotation systems to enable users to preserve said findings and review them at a later time. Even though the design of VR-based annotation systems has been a research topic for many years, crucial challenges remain unresolved. Many interaction solutions focus on isolated issues and are rather limited in scope. Additionally, they usually forgo holistic workflow designs that are vital for covering all relevant annotation operations in a consistent fashion. Similarly, available annotation presentation techniques are usually inappropriate for use within immersive virtual environments (IVEs) or they perform sub-optimally. Lastly, the design of annotation systems is usually further complicated if they are to be reused in context of other usage scenarios that impose a different and varying set of requirements on them. In this thesis, I set out to address the aforementioned issues. To this end, I present an annotation framework that was specifically designed to be configurable and extensible in accordance to the changing requirements of different application scenarios. It is grounded in a specialized data model that facilitates the integration not only of required data types, which are used to describe annotations, but also techniques to capture and present them. I employ this model to develop a flexible solution to the design of holistic interaction workflows. My design approach covers all essential operations, including the creation, modication, and review of arbitrary types of annotations from within IVEs. To provide a set of ready-to-use interaction techniques to acquire annotation contents, I identify the most relevant data types and devise appropriate interaction concepts. Similarly, I present a generalized two-tier presentation strategy that facilitates the access to and review of arbitrary annotation contents. While the tier one representation provides basic access to a selection of contents in a customizable form, the tier two representation allows for access to all contents in a generalized manner. I furthermore introduce a novel automated annotation layout approach that prevents occlusions of and by annotations to maintain visual access to them and the original data. In order to determine the viability of my approaches, I cover a series of technical analyses and user studies. They are rounded off by a presentation of concrete application examples that utilize varying subsets of techniques to demonstrate the usefulness and flexibility of my framework. Es laden ein: die Dozentinnen und Dozenten der Informatik

4 Jahre, 9 Monate

Einladung Informatik-Kolloquium Prof. Richard Fujimoto

von Mirko Stoffers

+********************************************************************** * * * Einladung * * * * Informatik-Kolloquium * * * +********************************************************************** Zeit: Freitag, 5. Juli 2019, 11.30 Uhr Ort: Informatikzentrum, E3, Raum 9007 Referent: Prof. Richard Fujimoto Georgia Institute of Technology, Atlanta Thema: Power Consumption in Parallel and Distributed Simulations Abstract: Energy and power consumption are important concerns for many computing systems ranging from battery-powered embedded and mobile devices to supercomputers and data centers. Although this issue has been extensively studied at the hardware and operating system levels, thus far only a limited amount of work has considered power consumption in parallel and distributed simulations. This presentation addresses this topic and discusses a variety of options to reduce power consumption. Further, parallel and distributed discrete event simulations require a synchronization algorithm to ensure the concurrent execution of the program produces the same results as a sequential execution. The energy consumed by synchronization algorithms for distributed simulation programs is considered, and experimental data presented highlighting that a significant portion of the energy consumed by distributed simulations can be attributed to synchronization. The concept of zero energy synchronization is introduced and techniques to reduce the energy consumed by synchronization algorithms are presented and evaluated. The presentation highlights that many open areas of research concerning power and energy consumption of distributed simulations remain to be explored. Speaker Biography: Richard Fujimoto is a Regents’ Professor in the School of Computational Science and Engineering at the Georgia Institute of Technology. He received the Ph.D. degree from the University of California at Berkeley in 1983. He has been an active researcher in the parallel and distributed simulation field since that time. He led the definition of the time management services in the High Level Architecture for Modeling and Simulation, IEEE standard 1516. His publications include seven award winning papers and he has received the ACM Distinguished Contributions in Modeling and Simulation Award. He has played various leadership roles in a variety of modeling and simulation conferences, journals and other activities. He was the founding chair of the School of Computational Science and Engineering (CSE) at Georgia Tech and established it as an academic unit devoted to the study of computer-based models of natural and engineered systems. In that role he led the creation of the interdisciplinary PhD and MS degree programs in CSE as well as two undergraduate minors. Es laden ein: die Dozentinnen und Dozenten der Informatik

4 Jahre, 9 Monate

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informatik-vortraege Juli 2019