informatik-vortraege November 2019

informatik-vortraege@lists.rwth-aachen.de

3 Teilnehmer
4 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, 11 Monate

Einladung: Informatik-Oberseminar Matthias Hoelzel

von Matthias Hoelzel

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Dienstag, 10. Dezember 2019, 12:00 Uhr Ort: Raum 9222, Gebäude E3, Ahornstr. 55 Referent: Matthias Hoelzel, M.Sc. LuF Math. Grundlagen der Informatik (Lehrgebiet Informatik 7) Thema: Fragments of Existential Second-Order Logic and Logics with Team Semantics Abstract: Team semantics is the modern basis for logics of dependence and independence whose formulae are not evaluated with single assignments, but with sets of such assignments. We study different fragments of logics with team semantics and existential second-order logic (ESO) such as the union-closed fragments of these logics, inclusion logic of restricted arity and logics with team semantics using weaker dependency concepts. We will present syntactic characterisations for the union-closed fragment of ESO and inclusion-exclusion logic. In order to obtain these characterisation results, novel inclusion-exclusion games are utilised as a bridge between semantical and syntactical fragments. These games are not only the model-checking games of ESO-sentences, but they can also be adapted for fragments of ESO and give rise to the definition of a single team-based atom that captures the union-closed fragment. Further we answer an open question due to Rönnholm regarding the connection between inclusion logic of restricted arity and a fragment of greatest fixed-point logic. Finally, we study variants of logics with dependency concepts, which can distinguish elements only up to a given equivalence. We juxtapose these new logics with equivalent fragments of ESO and analyse their expressive powers. Es laden ein: die Dozentinnen und Dozenten der Informatik

4 Jahre, 5 Monate

Einladung: Informatik Oberseminar Stefan Breuers

von Stefan Breuers

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Montag, 02. Dezember 2019, 13:30 Uhr Ort: UMIC Research Centre, room 025, Mies-van-der-Rohe Strasse 15 Referent: Stefan Breuers, MSc., Lehrstuhl Informatik 8 (Computer Vision) Thema: Multi-object Tracking and Person Analysis from Mobile Robot Platforms Abstract: Detecting and tracking the persons in a scene has been an active field of research in the area of computer vision for decades. One of the main applications are mobile platforms, such as autonomous cars or service robots. In this talk, we are going to analyze different tracking approaches working on the image domain and have a deeper look at their errors, before we move forward to multi-object tracking from robots operating in the 3D world. We present our detection-tracking framework for systematic tracking evaluation and our insights on experiments in challenging environments. On top of that detection-tracking pipeline, we then run person analysis modules and look at the benefits of such an integration for an improved person-robot interaction. By utilizing the temporal information in the form of the person track identities, we enable a robust and efficient operation of expensive deep learning analysis methods on low-cost platforms. We conclude the talk by presenting an explorative work on the integration of person re-identification and multi-object tracking to overcome common compromises of classical tracking approaches, taking a step towards an end-to-end, image-to-track paradigm. Es laden ein: die Dozentinnen und Dozenten der Informatik

4 Jahre, 5 Monate

Einladung: Informatik Oberseminar Herr Marius Alwin Shekow

von Daniele Gloeckner

4 Jahre, 5 Monate

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informatik-vortraege November 2019