informatik-vortraege

Download

informatik-vortraege@lists.rwth-aachen.de

August 2020

2 participants
2 discussions

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

3 15

Einladung Informatik-Oberseminar Jan Rüth
by Jan Rüth 06 Aug '20

06 Aug '20

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Freitag, 14. August 2020, 13.00 Uhr Zoom: https://rwth.zoom.us/j/94972202308?pwd=Y1o5cnBQYTYxdS9tYldaN0piQkozQT09 Referent: Jan Rüth, M.Sc. Lehrstuhl Informatik 4 Thema: Measuring the Evolution of the Internet in the Age of Giants Abstract: The Internet has evolved into an essential cornerstone of modern life. At its core, it is seemingly still powered by protocols developed in the late 1980s. Since then, the Internet has experienced a colossal visible evolution, e.g., from delivering small text files over dynamic websites to highly interactive and bulky content that define whole economic sectors. Notwithstanding, it is hard to believe that this change demanded no technological evolution, and in fact, research and industry have worked on many mechanisms and improvements to the core protocols. Today, we see Internet giants such as Google, Facebook, or Akamai controlling clients, servers, and networks driving these changes. Still, research has shown that these innovations often remain hard to deploy in practice as the Internet has condensed to supporting only a small set of protocols and parts of their features today. In this talk, we present novel Internet measurement methodologies to gain an understanding of how the Internet has evolved from textbook knowledge, how it deviates from standardized practices, and how these discovered discrepancies affect Internet operation. To this end, we recognize the critical role of Internet giants and specifically investigate their impact on core Internet technologies. In this presentation, we focus on the transport layer and examine TCP initial congestion window configurations, Congestion Control fairness, and QUIC as a new Internet transport. Lastly, we present how WebAssembly is largely abused for cryptocurrency mining in the Web today. Our contributions demonstrate that Internet giants coin practical Internet evolution. While they are keen to standardize their innovations, their configurations are often a well-kept secret. Their market dominance challenges the innovation of others, but even they are not immune to an abuse of their technology. Es laden ein: die Dozentinnen und Dozenten der Informatik

1 0