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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
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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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Zeit: Donnerstag, 12. März 2020, 10:45 Uhr
Ort: Raum 9222, Gebäude E3, Ahornstr. 55
Referent: Gereon Kremer, M.Sc.
Theory of Hybrid Systems
Thema: Cylindrical Algebraic Decomposition for Nonlinear Arithmetic
Problems
Abstract:
We explore the usage of the cylindrical algebraic decomposition method
for satisfiability modulo theories solving, both theoretically and
experimentally. This method is commonly understood as an almost atomic
procedure that gathers information about an algebraic problem and then
allows to answer all kinds of questions about this algebraic problem
afterwards. We essentially break up this method into smaller components
that we can then process in varying order to derive the particular piece
of information – whether the problem is satisfiable or unsatisfiable –
allowing to avoid some amount of computations. As this method often
exhibits doubly exponential running time, these savings can be
very significant in practice.
We then turn to an alternative approach to satisfiability modulo
theories solving commonly called model-constructing satisfiability
calculus. The core idea of this framework is to integrate the theory
reasoning, in particular the construction of a theory model, very
tightly with the Boolean reasoning. The main theory reasoning engine is
again based on the cylindrical algebraic decomposition method, though we
focus more on the overall framework here.
Es laden ein: die Dozentinnen und Dozenten der Informatik
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Gereon Kremer
Lehr- und Forschungsgebiet Theorie Hybrider Systeme
RWTH Aachen
Tel: +49 241 80 21243
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Zeit: Dienstag, 10. März 2020, 9.30 Uhr
Ort: Raum 2222, Ahornstr. 55 (Informatikgebäude, Hauptbau; Seminarraum i10)
Referent: Christian Corsten, M.Sc.
Lehrstuhl Informatik 10
Thema: Use the Force: How Force Touch Improves Input on Handheld Touchscreens
Abstract:
Handheld devices, such as smartphones, have become essential tools in our everyday life. We use them, e.g., to contact people, browse the web, or take pictures. For whatever use, to interact with the handheld device, we hold it with one or two hands and touch with our fingers on the built-in touchscreen. However, this interaction is often constrained to simple contact between the finger and the flat display glass, although touch offers further, richer properties. One such rich property is the intensity of a touch, i.e., its force, that the user applies with every tap to the touchscreen. Incorporating this property into the user’s interaction with the handheld device enables her to become more expressive with every single touch. In this thesis, we present a series of interaction techniques that take advantage of force touch input to make handheld interaction more efficient:
When holding the device with two hands in landscape orientation, most of the fingers are unavailable for interaction, since they rest at the back of the device (BoD), holding it in place. Using BoD force input, we can make efficient use of these fingers without sacrificing stability of the device grip. Our technique, BackXPress, enables quick access to shortcuts and menus to augment users’ touch interaction with the frontal screen.
For single-handed device use, users can only use their thumb to interact with the frontal touchscreen but cannot reach everywhere without re-grasping the device. Our virtual thumb extension, ForceRay, lets the user cast a ray at unreachable targets and control a cursor on that ray that moves closer to these targets the more force is applied. The technique is ergonomic for the thumb and enables users to maintain a steady device grip. Targets located at the screen edges, like menus and navigation buttons, are acquired quickly.
Selection of values from long ordered lists, such as picking a date or time, can also be sped up when using force input. With our Force Picker, users scroll through the value range at various speeds, with the speed being coupled to the force exerted by the thumb. Prior rolling of the thumb to the left or right sets the scrolling direction. Compared to touch-based pickers, our Force Picker not only makes selection faster, but also only consumes little screen space since the gesture footprint for force input is much smaller.
While controlling force via fingers requires practice, we show that with training and algorithmic optimizations, users become quickly familiar with force input and gain the benefits of the added expressiveness for handheld interaction.
Es laden ein: die Dozentinnen und Dozenten der Informatik
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Zeit: Freitag, 21. Februar 2020, 9.00 Uhr
Ort: IT Center Erweiterungsbau, Kopernikusstraße 6, S003
Referent: Daniel Zielasko, M.Sc.
Lehrstuhl Informatik 12
Thema: DeskVR: Seamless Integration of Virtual Reality into Desk-based Data
Analysis Workflows
Abstract:
In this work, we are looking into the possibilities and unique challenges
virtual reality today offers for (office) desk-based scenarios, as
they are ubiquitous in data analysis.
We characterize the scenario, introduce the term deskVR, and name
the technical challenges that come with it. Furthermore, we tackle
specific demands in two pillars of interaction in virtual reality,
selection & manipulation, and navigation. Then, we investigate
passive and active methods to prevent and reduce cybersickness, as
for us, tackling cybersickness is one if not the most critical tasks
that have to be solved to integrate virtual reality into everyday life
successfully. Finally, we apply the methods and findings made in this
thesis to a prototypical application framework for immersive 3D
graph exploration, serving as proof of concept for the integrability of
virtual reality into desk-based working scenarios. In the graph
visualization domain, we then also propose new vertex positioning
and edge bundling methods that address challenges arising with the
performed up-projection into 3D interactive space.
Es laden ein: die Dozentinnen und Dozenten der Informatik