@inproceedings{14898,
author = {{Schubert, Philipp and Leer, Richard and Hermann, Ben and Bodden, Eric}},
booktitle = {{Proceedings of the 8th ACM SIGPLAN International Workshop on State Of the Art in Program Analysis - SOAP 2019}},
isbn = {{9781450367202}},
title = {{{Know your analysis: how instrumentation aids understanding static analysis}}},
doi = {{10.1145/3315568.3329965}},
year = {{2019}},
}
@misc{15874,
author = {{Lienen, Christian}},
publisher = {{Universität Paderborn}},
title = {{{Implementing a Real-time System on a Platform FPGA operated with ReconOS}}},
year = {{2019}},
}
@article{21,
abstract = {{We address the general mathematical problem of computing the inverse p-th
root of a given matrix in an efficient way. A new method to construct iteration
functions that allow calculating arbitrary p-th roots and their inverses of
symmetric positive definite matrices is presented. We show that the order of
convergence is at least quadratic and that adaptively adjusting a parameter q
always leads to an even faster convergence. In this way, a better performance
than with previously known iteration schemes is achieved. The efficiency of the
iterative functions is demonstrated for various matrices with different
densities, condition numbers and spectral radii.}},
author = {{Richters, Dorothee and Lass, Michael and Walther, Andrea and Plessl, Christian and Kühne, Thomas}},
journal = {{Communications in Computational Physics}},
number = {{2}},
pages = {{564--585}},
publisher = {{Global Science Press}},
title = {{{A General Algorithm to Calculate the Inverse Principal p-th Root of Symmetric Positive Definite Matrices}}},
doi = {{10.4208/cicp.OA-2018-0053}},
volume = {{25}},
year = {{2019}},
}
@article{12871,
author = {{Platzner, Marco and Plessl, Christian}},
issn = {{0170-6012}},
journal = {{Informatik Spektrum}},
title = {{{FPGAs im Rechenzentrum}}},
doi = {{10.1007/s00287-019-01187-w}},
year = {{2019}},
}
@inproceedings{14848,
abstract = {{Data Science und Big Data durchdringt in ihren diversen Facetten unser tägliches Leben– kaum ein Tag, an dem nicht verschiedene Meldungen über technische Innovationen, Einsatzmöglichkeiten von Künstlicher Intelligenz (KI) und Maschinelles Lernen (ML) und ihre ethischen sowie gesellschaftlichen Implikationen in den unterschiedlichen Medien diskutiert werden. Aus diesem Grund erscheint es uns immens wichtig, diese Fragestellungen und Technologien auch in den Unterricht der Sekundarstufe II zu integrieren. Um diesem Anspruch gerecht zu werden, entwickelten wir im Rahmen eines Forschungsprojekts ein Curriculum, welches wir als konkretes Unterrichtskonzept innerhalb eines Projektkurses erprobt, evaluiert weiterentwickelt wird. Bei der Implementierung entschieden wir uns, zur aktiven Umsetzung von Konzepten von ML als Plattform Jupyter Notebook mit Python zu verwenden, da diese Umgebung durch die Verbindung von Code und Hypertext zur Dokumentation und Erklärung Medienbrüche im Lernprozess verringern kann. Zudem ist Python zur Implementierung der Methoden von ML sehr gut geeignet. Im Themenfeld des ML als Teilgebiet der KI legen wir den Fokus auf zwei unterschiedliche Lernverfahren um verschieden Aspekte von ML, u.A. wie Nachvollziehbarkeit unter gesellschaftlichen Gesichtspunkten zu vermitteln. Diese sind Künstliche Neuronale Netze (bei denen die Berechnung und Bedeutung der Kantengewichte zwischen den Neuronen für den Menschen insbesondere bei komplexeren Netzen kaum nachvollziehbar erschienen) und Entscheidungsbäume (strukturierte und gerichtete Bäume zur Darstellung von Entscheidungsregeln, welche auch für Schülerinnen und Schüler meist gut nachvollziehbares und verständliches KI-Modell darstellen). In diesem Workshop stellen wir konkrete Umsetzungsbeispiele inklusive der Programmierung für beide Verfahren mit Jupyter Notebook und Python als Teil einer Unterrichtssequenz vor und diskutieren diese.}},
author = {{Schlichtig, Michael and Opel, Simone and Schulte, Carsten and Biehler, Rolf and Frischemeier, Daniel and Podworny, Susanne and Wassong, Thomas}},
booktitle = {{Informatik für alle}},
editor = {{Pasternak, Arno}},
isbn = {{978-3-88579-682-4}},
location = {{Dortmund, Germany}},
pages = {{ 385 }},
publisher = {{Gesellschaft für Informatik}},
title = {{{Maschinelles Lernen im Unterricht mit Jupyter Notebook}}},
year = {{2019}},
}
@article{60388,
abstract = {{AbstractIn the field of global surface parametrization a recent focus has been on so‐called seamless parametrization. This term refers to parametrization approaches which, while using an atlas of charts to enable the handling of surfaces of arbitrary topology, relate the parametrization across the cuts between charts via transition functions from special classes of transformations. This effectively makes the cuts invisible to applications which are invariant to these specific transformations in some sense. In actual implementations of these parametrization approaches, however, these restrictions are obeyed only approximately; errors stem from the tolerances of numerical solvers employed and, ultimately, from the limited accuracy of floating point arithmetic. In practice, robustness issues arise from these flaws in the seamlessness of a parametrization, no matter how small. We present a robust global algorithm that turns a given approximately seamless parametrization into an exactly seamless one ‐ that still is representable by standard floating point numbers. It supports common practically relevant additional constraints regarding boundary and feature curve alignment or isocurve connectivity, and ensures that these are likewise fulfilled exactly. This allows subsequent algorithms to operate robustly on the resulting truly seamless parametrization. We believe that the core of our method will furthermore be of benefit in a broader range of applications involving linearly constrained numerical optimization.}},
author = {{Mandad, Manish and Campen, Marcel}},
issn = {{0167-7055}},
journal = {{Computer Graphics Forum}},
number = {{2}},
pages = {{135--145}},
publisher = {{Wiley}},
title = {{{Exact Constraint Satisfaction for Truly Seamless Parametrization}}},
doi = {{10.1111/cgf.13625}},
volume = {{38}},
year = {{2019}},
}
@article{60390,
abstract = {{
The problem of discrete surface parametrization, i.e. mapping a mesh to a planar domain, has been investigated extensively. We address the more general problem of mapping
between
surfaces. In particular, we provide a formulation that yields a map between two disk-topology meshes, which is continuous and injective by construction and which locally minimizes intrinsic distortion. A common approach is to express such a map as the composition of two maps via a simple intermediate domain such as the plane, and to independently optimize the individual maps. However, even if both individual maps are of minimal distortion, there is potentially high distortion in the composed map. In contrast to many previous works, we minimize distortion in an end-to-end manner, directly optimizing the quality of the composed map. This setting poses additional challenges due to the discrete nature of both the source and the target domain. We propose a formulation that, despite the combinatorial aspects of the problem, allows for a purely continuous optimization. Further, our approach addresses the non-smooth nature of discrete distortion measures in this context which hinders straightforward application of off-the-shelf optimization techniques. We demonstrate that, despite the challenges inherent to the more involved setting, discrete surface-to-surface maps can be optimized effectively.
}},
author = {{Schmidt, Patrick and Born, Janis and Campen, Marcel and Kobbelt, Leif}},
issn = {{0730-0301}},
journal = {{ACM Transactions on Graphics}},
number = {{6}},
pages = {{1--15}},
publisher = {{Association for Computing Machinery (ACM)}},
title = {{{Distortion-minimizing injective maps between surfaces}}},
doi = {{10.1145/3355089.3356519}},
volume = {{38}},
year = {{2019}},
}
@article{60389,
abstract = {{The generation of quad meshes based on surface parametrization techniques has proven to be a versatile approach. These techniques quantize an initial seamless parametrization so as to obtain an integer grid map implying a pure quad mesh. State-of-the-art methods following this approach have to assume that the surface to be meshed either has no boundary, or has a boundary which the resulting mesh is supposed to be aligned to. In a variety of applications this is not desirable and non-boundary-aligned meshes or grid-parametrizations are preferred. We thus present a technique to robustly generate integer grid maps which are either boundary-aligned, non-boundary-aligned, or partially boundary-aligned, just as required by different applications. We thereby generalize previous work to this broader setting. This enables the reliable generation of trimmed quad meshes with partial elements along the boundary, preferable in various scenarios, from tiled texturing over design and modeling to fabrication and architecture, due to fewer constraints and hence higher overall mesh quality and other benefits in terms of aesthetics and flexibility.}},
author = {{Lyon, Max and Campen, Marcel and Bommes, David and Kobbelt, Leif}},
issn = {{0730-0301}},
journal = {{ACM Transactions on Graphics}},
number = {{4}},
pages = {{1--14}},
publisher = {{Association for Computing Machinery (ACM)}},
title = {{{Parametrization quantization with free boundaries for trimmed quad meshing}}},
doi = {{10.1145/3306346.3323019}},
volume = {{38}},
year = {{2019}},
}
@article{60384,
abstract = {{Seamless global parametrization of surfaces is a key operation in geometry processing, e.g., for high-quality quad mesh generation. A common approach is to prescribe the parametric domain structure, in particular, the locations of parametrization singularities (cones), and solve a non-convex optimization problem minimizing a distortion measure, with local injectivity imposed through either constraints or barrier terms. In both cases, an initial valid parametrization is essential to serve as a feasible starting point for obtaining an optimized solution. While convexified versions of the constraints eliminate this initialization requirement, they narrow the range of solutions, causing some problem instances that actually do have a solution to become infeasible.
We demonstrate that for arbitrary given sets of topologically admissible parametric cones with prescribed curvature, a global seamless parametrization always exists (with the exception of one well-known case). Importantly, our proof is constructive and directly leads to a general algorithm for computing such parametrizations. Most distinctively, this algorithm is bootstrapped with a convex optimization problem (solving for a conformal map), in tandem with a simple linear equation system (determining a seamless modification of this map). This initial map can then serve as a valid starting point and be optimized for low distortion using existing injectivity preserving methods.}},
author = {{Campen, Marcel and Shen, Hanxiao and Zhou, Jiaran and Zorin, Denis}},
issn = {{0730-0301}},
journal = {{ACM Transactions on Graphics}},
number = {{1}},
pages = {{1--19}},
publisher = {{Association for Computing Machinery (ACM)}},
title = {{{Seamless Parametrization with Arbitrary Cones for Arbitrary Genus}}},
doi = {{10.1145/3360511}},
volume = {{39}},
year = {{2019}},
}
@inproceedings{2474,
author = {{Afifi, Haitham and Auroux, Sébastien and Karl, Holger}},
publisher = {{Proc. of IEEE Wireless Communications and Networking Conference (WCNC)}},
title = {{{MARVELO: Wireless Virtual Network Embedding for Overlay Graphs with Loops}}},
year = {{2018}},
}
@inproceedings{2476,
author = {{Shiferaw Heyi, Binyam and Karl, Holger}},
publisher = {{Proc. of IEEE Wireless Communications and Networking Conference (WCNC)}},
title = {{{Modelling Time-Limited Capacity of a Wireless Channel as aMarkov Reward Process}}},
year = {{2018}},
}
@inproceedings{2479,
author = {{Mohr, Felix and Wever, Marcel Dominik and Hüllermeier, Eyke and Faez, Amin}},
booktitle = {{SCC}},
location = {{San Francisco, CA, USA}},
publisher = {{IEEE}},
title = {{{(WIP) Towards the Automated Composition of Machine Learning Services}}},
doi = {{10.1109/SCC.2018.00039}},
year = {{2018}},
}
@inproceedings{2480,
abstract = {{Understanding the behavior of the components of service function chains (SFCs) in different load situations is important for efficient and automatic management and orches- tration of services. For this purpose and for practical research in network function virtualization in general, there is a great need for benchmarks and experimental data. In this paper, we describe our experiments for characterizing the relationship between resource demands of virtual network functions (VNFs) and the expected performance of the SFC, considering the individual performance of the VNFs as well as the interdependencies among VNFs within the SFC. We have designed our experiments focusing on video streaming, an important application in this context. We present examples of models for predicting the interdependence between resource demands and performance characteristics of SFCs using support vector regression and polynomial regression models. We also show practical evidence from our experiments that VNFs need to be benchmarked in their final chain setup, rather than individually, to capture important interdependencies that affect their performance. The data gathered from our experiments is publicly available.}},
author = {{Dräxler, Sevil and Peuster, Manuel and Illian, Marvin and Karl, Holger}},
booktitle = {{4th IEEE International Conference on Network Softwarization (NetSoft 2018)}},
location = {{Montreal}},
pages = {{318----322}},
publisher = {{IEEE}},
title = {{{Generating Resource and Performance Models for Service Function Chains: The Video Streaming Case}}},
doi = {{10.1109/NETSOFT.2018.8460029}},
year = {{2018}},
}
@inproceedings{2481,
abstract = {{Network function virtualization requires scaling and placement, deciding the number and the location of function instances. Current approaches are limited in flexibility and practical applicability. Specifically, we study dynamic, single-step, joint scaling and placement of network services with bidirectional flows traversing Physical or Virtual Network Functions (VNFs) and returning to their sources. We develop models to support stateful components and legacy network functions with fixed locations in these network services as well as the possibility of reusing VNFs across network services. We formalize the problem of jointly scaling and placing such network services as a mixed- integer linear program (MILP). We show that this problem is NP-complete and also present a heuristic algorithm to find good solutions in short time. In an extensive evaluation with realistic scenarios, we investigate the capabilities of the two approaches.}},
author = {{Dräxler, Sevil and Schneider, Stefan Balthasar and Karl, Holger}},
booktitle = {{4th IEEE International Conference on Network Softwarization (NetSoft 2018)}},
location = {{Montreal}},
pages = {{123----131}},
publisher = {{IEEE}},
title = {{{ Scaling and Placing Bidirectional Services with Stateful Virtual and Physical Network Functions}}},
year = {{2018}},
}
@techreport{2483,
abstract = {{Understanding the behavior of distributed cloud service components in different load situations is important for efficient and automatic management and orchestration of these services. For this purpose and for practical research in distributed cloud computing in general, there is need for benchmarks and experimental data. In this paper, we describe our experiments for characterizing the relationship between resource demands of application components and the expected performance of applica- tions. We present initial results for predicting the interdependence between resource demands and performance characteristics using support vector regression and polynomial regression models. The data gathered from our experiments is publicly available.}},
author = {{Dräxler, Sevil and Peuster, Manuel and Illian, Marvin and Karl, Holger}},
title = {{{Towards Predicting Resource Demands and Performance of Distributed Cloud Services}}},
year = {{2018}},
}
@inproceedings{2484,
abstract = {{We study the classic bin packing problem in a fully-dynamic setting, where new items can arrive and old items may depart. We want algorithms with low asymptotic competitive ratio while repacking items sparingly between updates. Formally, each item i has a movement cost c_i >= 0, and we want to use alpha * OPT bins and incur a movement cost gamma * c_i, either in the worst case, or in an amortized sense, for alpha, gamma as small as possible. We call gamma the recourse of the algorithm. This is motivated by cloud storage applications, where fully-dynamic bin packing models the problem of data backup to minimize the number of disks used, as well as communication incurred in moving file backups between disks. Since the set of files changes over time, we could recompute a solution periodically from scratch, but this would give a high number of disk rewrites, incurring a high energy cost and possible wear and tear of the disks. In this work, we present optimal tradeoffs between number of bins used and number of items repacked, as well as natural extensions of the latter measure.}},
author = {{Feldkord, Björn and Feldotto, Matthias and Gupta, Anupam and Guruganesh, Guru and Kumar, Amit and Riechers, Sören and Wajc, David}},
booktitle = {{45th International Colloquium on Automata, Languages, and Programming (ICALP 2018)}},
editor = {{Chatzigiannakis, Ioannis and Kaklamanis, Christos and Marx, Dániel and Sannella, Donald}},
isbn = {{978-3-95977-076-7}},
issn = {{1868-8969}},
location = {{Prag}},
pages = {{51:1--51:24}},
publisher = {{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik}},
title = {{{Fully-Dynamic Bin Packing with Little Repacking}}},
doi = {{10.4230/LIPIcs.ICALP.2018.51}},
volume = {{107}},
year = {{2018}},
}
@inproceedings{2485,
author = {{Feldkord, Björn and Meyer auf der Heide, Friedhelm}},
booktitle = {{Proceedings of the 30th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA)}},
location = {{Wien}},
pages = {{373 -- 381 }},
publisher = {{ACM}},
title = {{{Online Facility Location with Mobile Facilities}}},
doi = {{10.1145/3210377.3210389}},
year = {{2018}},
}
@misc{25121,
abstract = {{We consider a group of $n$ autonomous mobile robots of which $m$ are stationary thus cannot move. Robots are represented by points in the Euclidean plane. They have no memory, do not communicate or share a common coordinate system and they move solely based on the positioning of other robots within their limited viewing range of 1. The goal is to gather the robots inside of the convex hull of all stationary robots. A variant of this problem, the general gathering problem, has been studied in various different time models. In this work, we consider a continuous time model, where robots continuously observe their neighbors, compute the next target of movement and move with a speed limit of 1 at any time. Regarding the robots' local strategy, we only study contracting algorithms in which every robot that is positioned on the border of the convex hull of all robots moves into this hull. We present a time bound of $\mathcal{O}(nd)$ for any general contracting algorithms in a configuration with only a single stationary robot. For configurations with more stationary robots, we prove that robots converge against the convex hull of all stationary robots and that no upper bound on the runtime exists. For the specific contracting algorithms Go-To-The-Left, Go-On-Bisector and Go-To-The-Middle, we provide linear time bounds.}},
author = {{Liedtke, David Jan}},
title = {{{Influence of Stationary Robots on Continuous Robot Formation Problems}}},
year = {{2018}},
}
@unpublished{19524,
abstract = {{Object ranking is an important problem in the realm of preference learning.
On the basis of training data in the form of a set of rankings of objects,
which are typically represented as feature vectors, the goal is to learn a
ranking function that predicts a linear order of any new set of objects.
Current approaches commonly focus on ranking by scoring, i.e., on learning an
underlying latent utility function that seeks to capture the inherent utility
of each object. These approaches, however, are not able to take possible
effects of context-dependence into account, where context-dependence means that
the utility or usefulness of an object may also depend on what other objects
are available as alternatives. In this paper, we formalize the problem of
context-dependent ranking and present two general approaches based on two
natural representations of context-dependent ranking functions. Both approaches
are instantiated by means of appropriate neural network architectures, which
are evaluated on suitable benchmark task.}},
author = {{Pfannschmidt, Karlson and Gupta, Pritha and Hüllermeier, Eyke}},
booktitle = {{arXiv:1803.05796}},
title = {{{Deep Architectures for Learning Context-dependent Ranking Functions}}},
year = {{2018}},
}
@unpublished{19978,
abstract = {{We introduce the \emph{Online Connected Dominating Set Leasing} problem
(OCDSL) in which we are given an undirected connected graph $G = (V, E)$, a set
$\mathcal{L}$ of lease types each characterized by a duration and cost, and a
sequence of subsets of $V$ arriving over time. A node can be leased using lease
type $l$ for cost $c_l$ and remains active for time $d_l$. The adversary gives
in each step $t$ a subset of nodes that need to be dominated by a connected
subgraph consisting of nodes active at time $t$. The goal is to minimize the
total leasing costs. OCDSL contains the \emph{Parking Permit
Problem}~\cite{PPP} as a special subcase and generalizes the classical offline
\emph{Connected Dominating Set} problem~\cite{Guha1998}. It has an $\Omega(\log
^2 n + \log |\mathcal{L}|)$ randomized lower bound resulting from lower bounds
for the \emph{Parking Permit Problem} and the \emph{Online Set Cover}
problem~\cite{Alon:2003:OSC:780542.780558,Korman}, where $|\mathcal{L}|$ is the
number of available lease types and $n$ is the number of nodes in the input
graph. We give a randomized $\mathcal{O}(\log ^2 n + \log |\mathcal{L}| \log
n)$-competitive algorithm for OCDSL. We also give a deterministic algorithm for
a variant of OCDSL in which the dominating subgraph need not be connected, the
\emph{Online Dominating Set Leasing} problem. The latter is based on a simple
primal-dual approach and has an $\mathcal{O}(|\mathcal{L}| \cdot
\Delta)$-competitive ratio, where $\Delta$ is the maximum degree of the input
graph.}},
author = {{Markarian, Christine}},
booktitle = {{arXiv:1805.02994}},
title = {{{Online Connected Dominating Set Leasing}}},
year = {{2018}},
}