TY - GEN A1 - Hasler, Tim A1 - Amrhein, Kilian A1 - Klindt, Marco A1 - Oltmanns, Elias A1 - Peters-Kottig, Wolfgang T1 - Backup ist KEINE Langzeitverfügbarkeit N2 - Diese Handreichung im Flyerformat soll mit den verschiedenen Missverständnissen aufräumen, die einem im Alltag begegnen, wenn man es mit digitaler Langzeitverfügbarkeit zu tun hat. Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-99548 ER - TY - JOUR A1 - Donati, Luca A1 - Hartmann, Carsten A1 - Keller, Bettina G. T1 - Girsanov reweighting for path ensembles and Markov state models JF - The Journal of Chemical Physics N2 - The sensitivity of molecular dynamics on changes in the potential energy function plays an important role in understanding the dynamics and function of complex molecules. We present a method to obtain path ensemble averages of a perturbed dynamics from a set of paths generated by a reference dynamics. It is based on the concept of path probability measure and the Girsanov theorem, a result from stochastic analysis to estimate a change of measure of a path ensemble. Since Markov state models (MSMs) of the molecular dynamics can be formulated as a combined phase-space and path ensemble average, the method can be extended to reweight MSMs by combining it with a reweighting of the Boltzmann distribution. We demonstrate how to efficiently implement the Girsanov reweighting in a molecular dynamics simulation program by calculating parts of the reweighting factor “on the fly” during the simulation, and we benchmark the method on test systems ranging from a two-dimensional diffusion process and an artificial many-body system to alanine dipeptide and valine dipeptide in implicit and explicit water. The method can be used to study the sensitivity of molecular dynamics on external perturbations as well as to reweight trajectories generated by enhanced sampling schemes to the original dynamics. Y1 - 2017 U6 - https://doi.org/10.1063/1.4989474 VL - 146 IS - 24 SP - 244112 ER - TY - THES A1 - Löbel, Fabian T1 - Solving Integrated Timetabling and Passenger Routing Problems Using the Modulo Network Simplex Algorithm N2 - Common models and solving approaches for the problem of periodic timetabling, that is, determining periodic arrival and departure times of a given public transportation network’s lines so that the total weighted travel time of all passengers is minimized, fail to take passenger behavior into account. Current research is attempting to resolve this issue and first results show a positive impact on solution quality. This thesis aims to give a brief overview of literature on the topic of timetabling and to then state a heuristic approach to Integrated Timetabling by blending passenger behavior into the Modulo Network Simplex algorithm, which is part of the research carried out by the author’s study group at the Zuse Institut Berlin in the framework of MATHEON’s research project MI-3 supported by the Einstein Foundation Berlin. Y1 - 2017 ER - TY - CHAP A1 - Roy, Aurko A1 - Xu, Huan A1 - Pokutta, Sebastian T1 - Reinforcement Learning under Model Mismatch T2 - Proceedings of NIPS Y1 - 2017 N1 - Additional Note: http://https://papers.nips.cc/paper/by-source-2016-1199 https://arxiv.org/abs/1610.09269 ER - TY - CHAP A1 - Bärmann, Andreas A1 - Pokutta, Sebastian A1 - Schneider, Oskar T1 - Emulating the Expert: Inverse Optimization through Online Learning T2 - Proceedings of the International Conference on Machine Learning (ICML) Y1 - 2017 N1 - URL of the PDF: http://proceedings.mlr.press/v70/barmann17a.html N1 - URL of the Poster: https://app.box.com/s/h3ychkv99il7oyzw7sym8la5lhit3elg N1 - URL of the Slides: https://app.box.com/s/7ti8sz8mf5s2znn1qo32in4jxy5gjnn1 N1 - URL of the Abstract: http://www.pokutta.com/blog/research/2018/11/25/expertLearning-abstract.html ER - TY - CHAP A1 - Braun, Gábor A1 - Pokutta, Sebastian A1 - Zink, Daniel T1 - Lazifying Conditional Gradient Algorithms T2 - Proceedings of the International Conference on Machine Learning (ICML) Y1 - 2017 N1 - URL of the PDF: http://proceedings.mlr.press/v70/braun17a N1 - URL of the Poster: https://app.box.com/s/lysscdg17ytpz7mqr0tu2djffyqvkl6a N1 - URL of the Slides: https://app.box.com/s/zsp0hixjz2ha23u1vuyosijjkjdh8kj7 ER - TY - CHAP A1 - Arumugam, Keerthi Suria Kumar A1 - Kadampot, Ishaque Ashar A1 - Tahmasbi, Mehrdad A1 - Shah, Shaswat A1 - Bloch, Matthieu A1 - Pokutta, Sebastian T1 - Modulation Recognition Using Side Information and Hybrid Learning T2 - Proceedings of IEEE DySPAN Y1 - 2017 ER - TY - CHAP A1 - Lan, G. A1 - Pokutta, Sebastian A1 - Zhou, Y. A1 - Zink, Daniel T1 - Conditional Accelerated Lazy Stochastic Gradient Descent T2 - Proceedings of the International Conference on Machine Learning (ICML) Y1 - 2017 N1 - URL of the PDF: http://proceedings.mlr.press/v70/lan17a.html N1 - URL of the Poster: https://app.box.com/s/wnwym0p3eby54abb5bidnz7gznlkentq ER - TY - JOUR A1 - Roy, Aurko A1 - Pokutta, Sebastian T1 - Hierarchical Clustering via Spreading Metrics JF - Journal of Machine Learning Research (JMLR) Y1 - 2017 N1 - Additional Note: http://https://papers.nips.cc/paper/by-source-2016-1199 N1 - URL of the PDF: http://jmlr.org/papers/v18/17-081.html VL - 18 SP - 1 EP - 35 ER - TY - JOUR A1 - Bodur, Merve A1 - Del Pia, Alberto A1 - Dey, Santanu Sabush A1 - Molinaro, Marco A1 - Pokutta, Sebastian T1 - Aggregation-based cutting-planes for packing and covering Integer Programs JF - to appear in Mathematical Programming A Y1 - 2017 N1 - Additional Note: doi:10.1007/s10107-017-1192-x N1 - URL of the PDF: http://dx.doi.org/10.1007/s10107-017-1192-x ER - TY - JOUR A1 - Bazzi, Abbas A1 - Fiorini, Samuel A1 - Pokutta, Sebastian A1 - Svensson, Ola T1 - Small linear programs cannot approximate Vertex Cover within a factor of 2 - epsilon JF - to appear in Mathematics of Operations Research Y1 - 2017 N1 - URL of the Slides: https://app.box.com/s/00aqupo722bbpmdcyzwt8xmfqzyu14iy ER - TY - JOUR A1 - Braun, Gábor A1 - Guzmán, C. A1 - Pokutta, Sebastian T1 - Unifying Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization JF - IEEE Transactions of Information Theory Y1 - 2017 N1 - Additional Note: doi:10.1109/TIT.2017.2701343 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7919238 N1 - URL of the PDF: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7919238 VL - 63 IS - 7 SP - 4709 EP - 4724 ER - TY - JOUR A1 - Braun, Gábor A1 - Jain, R. A1 - Lee, T. A1 - Pokutta, Sebastian T1 - Information-theoretic approximations of the nonnegative rank JF - Computational Complexity Y1 - 2017 UR - http://eccc.hpi-web.de/report/2013/158 VL - 26 IS - 1 SP - 147 EP - 197 ER - TY - JOUR A1 - Christensen, H. A1 - Khan, A. A1 - Pokutta, Sebastian A1 - Tetali, P. T1 - Multidimensional Bin Packing and Other Related Problems: A survey JF - to appear in Computer Science Review Y1 - 2017 N1 - Additional Note: http://www.sciencedirect.com/science/article/pii/S1574013716301356 http://www.sciencedirect.com/science/article/pii/S1574013716301356 N1 - URL of the PDF: http://www.sciencedirect.com/science/article/pii/S1574013716301356 ER - TY - JOUR A1 - Martin, Alex A1 - Müller, J. A1 - Pape, S. A1 - Peter, A. A1 - Pokutta, Sebastian A1 - Winter, T. T1 - Pricing and clearing combinatorial markets with singleton and swap orders JF - Mathematical Methods of Operations Research Y1 - 2017 VL - 85 IS - 2 SP - 155 EP - 177 ER - TY - JOUR A1 - Knueven, B. A1 - Ostrowski, J. A1 - Pokutta, Sebastian T1 - Detecting Almost Symmetries in Graphs JF - to appear in Mathematical Programming C Y1 - 2017 UR - http://www.optimization-online.org/DB_HTML/2015/09/5117.html N1 - URL of the PDF: http://link.springer.com/article/10.1007/s12532-017-0124-3 ER - TY - JOUR A1 - Braun, Gábor A1 - Brown-Cohen, Jonah A1 - Huq, Arefin A1 - Pokutta, Sebastian A1 - Raghavendra, Prasad A1 - Weitz, Benjamin A1 - Zink, Daniel T1 - The matching problem has no small symmetric SDP JF - Mathematical Programming A Y1 - 2017 N1 - Additional Note: DOI 10.1007/s10107-016-1098-z N1 - URL of the PDF: http://dx.doi.org/10.1007/s10107-016-1098-z VL - 165 IS - 2 SP - 643 EP - 662 ER - TY - GEN A1 - Christof, Jürgen A1 - Conrad-Rempel, Steffi A1 - Degkwitz, Andreas A1 - Goltz-Fellgiebel, Julia Alexandra A1 - Happel, Hans-Gerd A1 - Hasler, Tim A1 - Heiss, Alexandra A1 - Kaminsky, Uta A1 - Kant, Oliver A1 - Kende, Jiří A1 - Koch, Thorsten A1 - Kuberek, Monika A1 - Lohrum, Stefan A1 - Müller, Anja A1 - Mutter, Moritz A1 - Peters-Kottig, Wolfgang A1 - Quitzsch, Nicole A1 - Rusch, Beate A1 - Schwidder, Jens A1 - Stanek, Ursula A1 - Weihe, Signe A1 - Zeyns, Andrea T1 - KOBV Jahresbericht 2015-2016 N2 - Der KOBV-Jahresbericht informiert rückblickend im 2-Jahres-Rhythmus über die bibliothekarisch-fachlichen Entwicklungen im Verbund und die Projekte des Kooperativen Bibliotheksverbunds Berlin-Brandenburg (KOBV). T3 - KOBV-Jahresbericht - 2015-2016 KW - KOBV KW - Jahresbericht Y1 - 2017 SN - 0934-5892 VL - 2015-2016 IS - 2015-2016 SP - 1 EP - 64 ER - TY - JOUR A1 - Bernal, David E. A1 - Vigerske, Stefan A1 - Trespalacios, Francisco A1 - Grossmann, Ignacio E. T1 - Improving the performance of DICOPT in convex MINLP problems using a feasibility pump JF - Optimization Methods and Software N2 - The solver DICOPT is based on an outer-approximation algorithm used for solving mixed- integer nonlinear programming (MINLP) problems. This algorithm is very effective for solving some types of convex MINLPs. However, there are certain problems that are diffcult to solve with this algorithm. One of these problems is when the nonlinear constraints are so restrictive that the nonlinear subproblems produced by the algorithm are infeasible. This problem is addressed in this paper with a feasibility pump algorithm, which modifies the objective function in order to efficiently find feasible solutions. It has been implemented as a preprocessing algorithm for DICOPT. Computational comparisons with previous versions of DICOPT and other MINLP solvers on a set of convex MINLPs demonstrate the effectiveness of the proposed algorithm in terms of solution quality and solving time. Y1 - 2017 ER - TY - GEN A1 - Sakurai, Daisuke A1 - Hege, Hans-Christian A1 - Kuhn, Alexander A1 - Rust, Henning A1 - Kern, Bastian A1 - Breitkopf, Tom-Lukas T1 - An Application-Oriented Framework for Feature Tracking in Atmospheric Sciences N2 - In atmospheric sciences, sizes of data sets grow continuously due to increasing resolutions. A central task is the comparison of spatiotemporal fields, to assess different simulations and to compare simulations with observations. A significant information reduction is possible by focusing on geometric-topological features of the fields or on derived meteorological objects. Due to the huge size of the data sets, spatial features have to be extracted in time slices and traced over time. Fields with chaotic component, i.e. without 1:1 spatiotemporal correspondences, can be compared by looking upon statistics of feature properties. Feature extraction, however, requires a clear mathematical definition of the features – which many meteorological objects still lack. Traditionally, object extractions are often heuristic, defined only by implemented algorithms, and thus are not comparable. This work surveys our framework designed for efficient development of feature tracking methods and for testing new feature definitions. The framework supports well-established visualization practices and is being used by atmospheric researchers to diagnose and compare data. T3 - ZIB-Report - 17-50 Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-72617 SN - 1438-0064 ER - TY - JOUR A1 - Chrapary, Hagen A1 - Dalitz, Wolfgang A1 - Neun, Winfried A1 - Sperber, Wolfram T1 - Design, Concepts, and State of the Art of the swMATH Service JF - Mathematics in Computer Science N2 - In this paper, the concepts and design for an efficient information service for mathematical software and further mathematical research data are presented. The publication-based approach and the web-based approach are the main building blocks of the service and will be discussed. Heuristic methods are used for identification, extraction, and ranking of information about software and other mathematical research data. The methods provide not only information about the research data but also link software and mathematical research data to the scientific context. Y1 - 2017 U6 - https://doi.org/10.1007/s11786-017-0305-5 VL - 11 IS - 3-4 SP - 469 EP - 481 ER - TY - JOUR A1 - Seeber, L. A1 - Conrad, Tim A1 - Hoppe, Christian A1 - Obermeier, Patrick A1 - Chen, X. A1 - Karsch, K. A1 - Muehlhans, S. A1 - Tief, Franziska A1 - Boettcher, Sindy A1 - Diedrich, S. A1 - Schweiger, Brunhilde A1 - Rath, Barbara T1 - Educating parents about the vaccination status of their children: A user-centered mobile application JF - Preventive Medicine Reports N2 - Parents are often uncertain about the vaccination status of their children. In times of vaccine hesitancy, vaccination programs could benefit from active patient participation. The Vaccination App (VAccApp) was developed by the Vienna Vaccine Safety Initiative, enabling parents to learn about the vaccination status of their children, including 25 different routine, special indication and travel vaccines listed in the WHO Immunization Certificate of Vaccination (WHO-ICV). Between 2012 and 2014, the VAccApp was validated in a hospital-based quality management program in Berlin, Germany, in collaboration with the Robert Koch Institute. Parents of 178 children were asked to transfer the immunization data of their children from the WHO-ICV into the VAccApp. The respective WHO-ICV was photocopied for independent, professional data entry (gold standard). Demonstrating the status quo in vaccine information reporting, a Recall Group of 278 parents underwent structured interviews for verbal immunization histories, without the respective WHO-ICV. Only 9% of the Recall Group were able to provide a complete vaccination status; on average 39% of the questions were answered correctly. Using the WHO-ICV with the help of the VAccApp resulted in 62% of parents providing a complete vaccination status; on average 95% of the questions were answered correctly. After using the VAccApp, parents were more likely to remember key aspects of the vaccination history. User-friendly mobile applications empower parents to take a closer look at the vaccination record, thereby taking an active role in providing accurate vaccination histories. Parents may become motivated to ask informed questions and to keep vaccinations up-to-date. Y1 - 2017 U6 - https://doi.org/10.1016/j.pmedr.2017.01.002 VL - 5 SP - 241 EP - 250 ER - TY - JOUR A1 - Conrad, Tim A1 - Genzel, Martin A1 - Cvetkovic, Nada A1 - Wulkow, Niklas A1 - Vybiral, Jan A1 - Kutyniok, Gitta A1 - Schütte, Christof T1 - Sparse Proteomics Analysis – a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data JF - BMC Bioinformatics N2 - Motivation: High-throughput proteomics techniques, such as mass spectrometry (MS)-based approaches, produce very high-dimensional data-sets. In a clinical setting one is often interested how MS spectra dier between patients of different classes, for example spectra from healthy patients vs. spectra from patients having a particular disease. Machine learning algorithms are needed to (a) identify these discriminating features and (b) classify unknown spectra based on this feature set. Since the acquired data is usually noisy, the algorithms should be robust to noise and outliers, and the identied feature set should be as small as possible. Results: We present a new algorithm, Sparse Proteomics Analysis (SPA), based on the theory of Compressed Sensing that allows to identify a minimal discriminating set of features from mass spectrometry data-sets. We show how our method performs on artificial and real-world data-sets. Y1 - 2017 U6 - https://doi.org/10.1186/s12859-017-1565-4 VL - 18 IS - 160 SP - 1 EP - 20 ER - TY - JOUR A1 - Borong, Shao A1 - Cannistraci, Carlo A1 - Conrad, Tim T1 - Epithelial Mesenchymal Transition Network-based Feature Engineering in Lung Adenocarcinoma Prognosis Prediction Using Multiple Omic Data JF - Genomics and Computational Biology N2 - Epithelial mesenchymal transition (EMT) process has been shown as highly relevant to cancer prognosis. However, although different biological network-based biomarker identification methods have been proposed to predict cancer prognosis, EMT network has not been directly used for this purpose. In this study, we constructed an EMT regulatory network consisting of 87 molecules and tried to select features that are useful for prognosis prediction in Lung Adenocarcinoma (LUAD). To incorporate multiple molecular profiles, we obtained four types of molecular data including mRNA-Seq, copy number alteration (CNA), DNA methylation, and miRNA-Seq data from The Cancer Genome Atlas. The data were mapped to the EMT network in three alternative ways: mRNA-Seq and miRNA-Seq, DNA methylation, and CNA and miRNA-Seq. Each mapping was employed to extract five different sets of features using discretization and network-based biomarker identification methods. Each feature set was then used to predict prognosis with SVM and logistic regression classifiers. We measured the prediction accuracy with AUC and AUPR values using 10 times 10-fold cross validation. For a more comprehensive evaluation, we also measured the prediction accuracies of clinical features, EMT plus clinical features, randomly picked 87 molecules from each data mapping, and using all molecules from each data type. Counter-intuitively, EMT features do not always outperform randomly selected features and the prediction accuracies of the five feature sets are mostly not significantly different. Clinical features are shown to give the highest prediction accuracies. In addition, the prediction accuracies of both EMT features and random features are comparable as using all features (more than 17,000) from each data type. Y1 - 2017 U6 - https://doi.org/http://dx.doi.org/10.18547/gcb.2017.vol3.iss3.e57 VL - 3 IS - 3 SP - 1 EP - 13 ER - TY - CHAP A1 - Jayrannejad, Fahrnaz A1 - Conrad, Tim T1 - Better Interpretable Models for Proteomics Data Analysis Using rule-based Mining T2 - Springer Lecture Notes in Artificial Intelligence N2 - Recent advances in -omics technology has yielded in large data-sets in many areas of biology, such as mass spectrometry based proteomics. However, analyzing this data is still a challenging task mainly due to the very high dimensionality and high noise content of the data. One of the main objectives of the analysis is the identification of relevant patterns (or features) which can be used for classification of new samples to healthy or diseased. So, a method is required to find easily interpretable models from this data. To gain the above mentioned goal, we have adapted the disjunctive association rule mining algorithm, TitanicOR, to identify emerging patterns from our mass spectrometry proteomics data-sets. Comparison to five state-of-the-art methods shows that our method is advantageous them in terms of identifying the inter-dependency between the features and the TP-rate and precision of the features selected. We further demonstrate the applicability of our algorithm to one previously published clinical data-set. Y1 - 2017 SP - studi ER - TY - THES A1 - Jeschke, Björn-Marcel T1 - Alternativen zum Dijkstra Algorithmus in der (Nah-) Verkehrsoptimierung N2 - In dieser Arbeit betrachten wir das Problem, für den Fahrplan eines (Nah-) Verkehrsnetzes schnellste Wege zu berechnen. Da die Verkehrsmittel zu unterschiedlichen Zeiten von den einzelnen Haltestellen/Bahnhöfen abfahren, kann das Problem nicht ohne Weiteres mit einem „statischen“ Graphen modelliert werden. Es gibt zwei unterschiedliche Ansätze für dieses zeitabhängige Problem: Erstens können die verschiedenen An-/Abfahrtereignisse an einem Halt durch „Kopien“ dargestellt werden, das ist das zeit-expandierte Modell. Zweitens können die Gewichte der Kanten zeitabhängig sein, das ist das zeitabhängige Modell. Wir untersuchen in dieser Arbeit, wie der „klassische“ Dijkstra-Algorithmus und der A* Algorithmus mit einer geeigneten Heuristik im Vergleich abschneiden. Die gewählte Heuristik ist der Abstand zum Zielknoten, wenn die Abfahrtszeiten ignoriert werden. Nach unseren Untersuchungen zeigt sich, dass der A* Algorithmus dem Dijkstra-Algorithmus weit überlegen ist für genügend große Nahverkehrsnetze. Wir testen anhand der echten Verkehrsnetze von Berlin und Aachen. Unsere Berechnungen zeigen, dass die gewählte Heuristik besonders gut ist für Start- und Zielknoten, welche unabhängig von ihrer Distanz nur 1–2 verschiedene mögliche kürzeste Pfade für alle Zeitschritte haben. Dort ist der A* Algorithmus bis zu 20-mal schneller. Dies kommt aber nicht häufig in unseren Testinstanzen vor. Die einzelnen Laufzeitvergleich zeigen, dass der A* Algorithmus durchschnittlich 7-mal so schnell ist wie der Dikstra-Algorithmus. Y1 - 2017 ER - TY - JOUR A1 - Apprich, Christian A1 - Dieterich, Annegret A1 - Höllig, Klaus A1 - Nava-Yazdani, Esfandiar T1 - Cubic spline approximation of a circle with maximal smoothness and accuracy JF - Computer Aided Geometric Design N2 - We construct cubic spline approximations of a circle which are four times continuously differentiable and converge with order six. Y1 - 2017 U6 - https://doi.org/10.1016/j.cagd.2017.05.001 VL - 56 SP - 1 EP - 3 PB - Elsevier B.V. ER - TY - GEN A1 - Sahu, Manish A1 - Dill, Sabrina A1 - Mukhopadyay, Anirban A1 - Zachow, Stefan T1 - Surgical Tool Presence Detection for Cataract Procedures N2 - This article outlines the submission to the CATARACTS challenge for automatic tool presence detection [1]. Our approach for this multi-label classification problem comprises labelset-based sampling, a CNN architecture and temporal smothing as described in [3], which we call ZIB-Res-TS. T3 - ZIB-Report - 18-28 Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-69110 SN - 1438-0064 ER - TY - JOUR A1 - D'Andreagiovanni, Fabio A1 - Mett, Fabian A1 - Nardin, Antonella A1 - Pulaj, Jonad T1 - Integrating LP-guided variable fixing with MIP heuristics in the robust design of hybrid wired-wireless FTTx access networks JF - Applied Soft Computing N2 - This study investigates how to model and solve the problem of optimally designing FTTx telecommunications access networks integrating wired and wireless technologies, while taking into account the uncertainty of wireless signal propagation. We propose an original robust optimization model for the related robust 3-architecture Connected Facility Location problem, which includes additional variables and constraints to model wireless signal coverage represented through signal-to-interference ratios. Since the resulting robust problem can prove very challenging even for a modern state-of-the art optimization solver, we propose to solve it by an original primal heuristic that combines a probabilistic variable fixing procedure, guided by peculiar Linear Programming relaxations, with a Mixed Integer Programming heuristic, based on an exact very large neighborhood search. A numerical study carried out on a set of realistic instances show that our heuristic can find solutions of much higher quality than a state-of-the-art solver. Y1 - 2017 U6 - https://doi.org/10.1016/j.asoc.2017.07.018 VL - 61 SP - 1074 EP - 1087 ER - TY - THES A1 - Reuther, Markus T1 - Mathematical Optimization of Rolling Stock Rotations N2 - We show how to optimize rolling stock rotations that are required for the operation of a passenger timetable. The underlying mathematical ptimization problem is called rolling stock rotation problem (RSRP) and the leitmotiv of the thesis is RotOR, i.e., a highly integrated optimization algorithm for the RSRP. RotOR is used by DB Fernverkehr AG (DBF) in order to optimize intercity express (ICE) rotations for the European high-speed network. In this application, RSRPs have to be solved which (A) require many different aspects to be simultaneously considered, (B) are typically of large scale, and (C) include constraints that have a difficult combinatorial structure. This thesis suggests answers to these issues via the following concepts. (A) The main model, which RotOR uses, relies on a hypergraph. The hypergraph provides an easy way to model manifold industrial railway requirements in great detail. This includes well known vehicle composition requirements as well as relatively unexplored regularity stipulations. At the same time, the hypergraph directly leads to a mixed-integer programming (MIP) model for the RSRP. (B) The main algorithmic ingredient to solve industrial instances of the RSRP is a coarse-to-fine (C2F) column generation procedure. In this approach, the hypergraph is layered into coarse and fine layers that distinguish different levels of detail of the RSRP. The coarse layers are algorithmically utilized while pricing fine columns until proven optimality. Initially, the C2F approach is presented in terms of pure linear programming in order to provide an interface for other applications. (C) Rolling stock rotations have to comply to resource constraints in order to ensure, e.g., enough maintenance inspections along the rotations. These constraints are computationally hard, but are well known in the literature on the vehicle routing problem (VRP). We define an interface problem in order to bridge between the RSRP and the VRP and derive a straightforward algorithmic concept, namely regional search (RS), from their common features and, moreover, differences. Our RS algorithms show promising results for classical VRPs and RSRPs. In the first part of the thesis we present these concepts, which encompass its main mathematical contribution. The second part explains all modeling and solving components of RotOR that turn out to be essential in its industrial application. The thesis concludes with a solution to a complex re-optimization RSRP that RotOR has computed successfully for DBF. In this application all ICE vehicles of the ICE-W fleets of DBF had to be redirected past a construction site on a high-speed line in the heart of Germany. Y1 - 2017 UR - https://depositonce.tu-berlin.de/handle/11303/6309 ER - TY - JOUR A1 - Sullivan, T. J. T1 - Well-posed Bayesian inverse problems and heavy-tailed stable quasi-Banach space priors JF - Inverse Problems and Imaging Y1 - 2017 U6 - https://doi.org/10.3934/ipi.2017040 VL - 11 IS - 5 SP - 857 EP - 874 ER - TY - CHAP A1 - Sullivan, T. J. T1 - Well-posedness of Bayesian inverse problems in quasi-Banach spaces with stable priors T2 - 88th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), Weimar 2017 Y1 - 2017 U6 - https://doi.org/10.1002/pamm.201710402 VL - 17 IS - 1 SP - 871 EP - 874 ER - TY - JOUR A1 - Jayrannejad, Fahrnaz A1 - Conrad, Tim T1 - Better Interpretable Models for Proteomics Data Analysis Using rule-based Mining JF - Springer Lecture Notes in Artificial Intelligence N2 - Recent advances in -omics technology has yielded in large data-sets in many areas of biology, such as mass spectrometry based proteomics. However, analyzing this data is still a challenging task mainly due to the very high dimensionality and high noise content of the data. One of the main objectives of the analysis is the identification of relevant patterns (or features) which can be used for classification of new samples to healthy or diseased. So, a method is required to find easily interpretable models from this data. To gain the above mentioned goal, we have adapted the disjunctive association rule mining algorithm, TitanicOR, to identify emerging patterns from our mass spectrometry proteomics data-sets. Comparison to five state-of-the-art methods shows that our method is advantageous them in terms of identifying the inter-dependency between the features and the TP-rate and precision of the features selected. We further demonstrate the applicability of our algorithm to one previously published clinical data-set. Y1 - 2017 ER - TY - JOUR A1 - Shao, Borong A1 - Cannistraci, Carlo Vittorio A1 - Conrad, Tim T1 - Epithelial Mesenchymal Transition Network-Based Feature Engineering in Lung Adenocarcinoma Prognosis Prediction Using Multiple Omic Data JF - Genomics and Computational Biology N2 - Epithelial mesenchymal transition (EMT) process has been shown as highly relevant to cancer prognosis. However, although different biological network-based biomarker identification methods have been proposed to predict cancer prognosis, EMT network has not been directly used for this purpose. In this study, we constructed an EMT regulatory network consisting of 87 molecules and tried to select features that are useful for prognosis prediction in Lung Adenocarcinoma (LUAD). To incorporate multiple molecular profiles, we obtained four types of molecular data including mRNA-Seq, copy number alteration (CNA), DNA methylation, and miRNA-Seq data from The Cancer Genome Atlas. The data were mapped to the EMT network in three alternative ways: mRNA-Seq and miRNA-Seq, DNA methylation, and CNA and miRNA-Seq. Each mapping was employed to extract five different sets of features using discretization and network-based biomarker identification methods. Each feature set was then used to predict prognosis with SVM and logistic regression classifiers. We measured the prediction accuracy with AUC and AUPR values using 10 times 10-fold cross validation. For a more comprehensive evaluation, we also measured the prediction accuracies of clinical features, EMT plus clinical features, randomly picked 87 molecules from each data mapping, and using all molecules from each data type. Counter-intuitively, EMT features do not always outperform randomly selected features and the prediction accuracies of the five feature sets are mostly not significantly different. Clinical features are shown to give the highest prediction accuracies. In addition, the prediction accuracies of both EMT features and random features are comparable as using all features (more than 17,000) from each data type. Y1 - 2017 U6 - https://doi.org/10.18547/gcb.2017.vol3.iss3.e57 VL - 3 IS - 3 SP - e57 ER - TY - JOUR A1 - Rath, Barbara A1 - Conrad, Tim A1 - Myles, Puja A1 - Alchikh, Maren A1 - Ma, Xiaolin A1 - Hoppe, Christian A1 - Tief, Franziska A1 - Chen, Xi A1 - Obermeier, Patrick A1 - Kisler, Bron A1 - Schweiger, Brunhilde T1 - Influenza and other respiratory viruses: standardizing disease severity in surveillance and clinical trials JF - Expert Review of Anti-infective Therapy N2 - Introduction: Influenza-Like Illness is a leading cause of hospitalization in children. Disease burden due to influenza and other respiratory viral infections is reported on a population level, but clinical scores measuring individual changes in disease severity are urgently needed. Areas covered: We present a composite clinical score allowing individual patient data analyses of disease severity based on systematic literature review and WHO-criteria for uncomplicated and complicated disease. The 22-item ViVI Disease Severity Score showed a normal distribution in a pediatric cohort of 6073 children aged 0–18 years (mean age 3.13; S.D. 3.89; range: 0 to 18.79). Expert commentary: The ViVI Score was correlated with risk of antibiotic use as well as need for hospitalization and intensive care. The ViVI Score was used to track children with influenza, respiratory syncytial virus, human metapneumovirus, human rhinovirus, and adenovirus infections and is fully compliant with regulatory data standards. The ViVI Disease Severity Score mobile application allows physicians to measure disease severity at the point-of care thereby taking clinical trials to the next level. KW - Disease severity KW - influenza-like illness KW - influenza KW - respiratory syncytial virus KW - human metapneumovirus KW - human rhinovirus KW - adenovirus KW - seasonality KW - antivirals KW - clinical trials Y1 - 2017 U6 - https://doi.org/10.1080/14787210.2017.1295847 VL - 15 IS - 6 SP - 545 EP - 568 ER - TY - CHAP A1 - Papazov, Chavdar A1 - Hege, Hans-Christian T1 - Blue-noise Optimized Point Sets Based on Procrustes Analysis T2 - SIGGRAPH Asia 2017 Technical Briefs Y1 - 2017 U6 - https://doi.org/10.1145/3145749.3149442 SP - 20:1 EP - 20:4 ER - TY - GEN A1 - Weber, Marcus A1 - Durmaz, Vedat A1 - Sabri, Peggy A1 - Reidelbach, Marco T1 - Supplementary simulation data for Science Manuscript ai8636 N2 - The simulation data has been produced by Vedat Durmaz, Peggy Sabri and Marco Reidelbach inside the "Computational Molecular Design" Group headed by Marcus Weber at Zuse-Institut Berlin, Takustr. 7, D-14195 Berlin, Germany. The file contains classical simulation data for different fentanyl derivates in the MOR binding pocket at different pHs. It also includes instruction files for quantum-chemical pKa-value estimations and a description of how we derived the pKa-values from the Gaussian09 log-files. Y1 - 2017 U6 - https://doi.org/10.12752/5.MWB.1.0 N1 - GROMACS trajectories and GAUSSIAN files of MOR and fentanyl derivates ER - TY - THES A1 - Pulaj, Jonad T1 - Cutting Planes for Union-Closed Families N2 - Frankl’s (union-closed sets) conjecture states that for any nonempty finite union-closed (UC) family of distinct sets there exists an element in at least half of the sets. Poonen’s Theorem characterizes the existence of weights which determine whether a given UC family ensures Frankl’s conjecture holds for all UC families which contain it. The weight systems are nontrivial to identify for a given UC family, and methods to determine such weight systems have led to several other open questions and conjectures regarding structures in UC families. We design a cutting-plane method that computes the explicit weights which imply the existence conditions of Poonen’s Theorem using computational integer programming coupled with redundant verification routines that ensure correctness. We find over one hundred previously unknown families of sets which ensure Frankl’s conjecture holds for all families that contain any of them. This improves significantly on all previous results of the kind. Our framework allows us to answer several open questions and conjectures regarding structural properties of UC families, including proving the 3-sets conjecture of Morris from 2006 which characterizes the minimum number of 3-sets that ensure Frankl’s conjecture holds for all families that contain them. Furthermore, our method provides a general algorithmic road-map for improving other known results and uncovering structures in UC families. Y1 - 2017 UR - https://depositonce.tu-berlin.de//handle/11303/7258 ER - TY - THES A1 - Schubert, Christoph T1 - Multi-Level Lookahead Branching Y1 - 2017 ER - TY - THES A1 - Wischlinsky, William T1 - Feasibility-based bound tightening via linear programming Y1 - 2017 ER - TY - CHAP A1 - Cheung, Kevin K. H. A1 - Gleixner, Ambros A1 - Steffy, Daniel T1 - Verifying Integer Programming Results T2 - F. Eisenbrand and J. Koenemann, eds., Integer Programming and Combinatorial Optimization: 19th International Conference, IPCO 2017 N2 - Software for mixed-integer linear programming can return incorrect results for a number of reasons, one being the use of inexact floating-point arithmetic. Even solvers that employ exact arithmetic may suffer from programming or algorithmic errors, motivating the desire for a way to produce independently verifiable certificates of claimed results. Due to the complex nature of state-of-the-art MIP solution algorithms, the ideal form of such a certificate is not entirely clear. This paper proposes such a certificate format designed with simplicity in mind, which is composed of a list of statements that can be sequentially verified using a limited number of inference rules. We present a supplementary verification tool for compressing and checking these certificates independently of how they were created. We report computational results on a selection of MIP instances from the literature. To this end, we have extended the exact rational version of the MIP solver SCIP to produce such certificates. Y1 - 2017 U6 - https://doi.org/10.1007/978-3-319-59250-3_13 VL - 10328 SP - 148 EP - 160 ER - TY - JOUR A1 - Vierhaus, Ingmar A1 - Fügenschuh, Armin A1 - Gottwald, Robert Lion A1 - Grösser, Stefan T1 - Using white-box nonlinear optimization methods in system dynamics policy improvement JF - System Dynamics Review N2 - We present a new strategy for the direct optimization of the values of policy functions. This approach is particularly well suited to model actors with a global perspective on the system and relies heavily on modern mathematical white-box optimization methods. We demonstrate our strategy on two classical models: market growth and World2. Each model is first transformed into an optimization problem by defining how the actor can influence the models' dynamics and by choosing objective functions to measure improvements. To improve comparability between different runs, we also introduce a comparison measure for possible interventions. We solve the optimization problems, discuss the resulting policies and compare them to the existing results from the literature. In particular, we present a run of the World2 model which significantly improves the published “towards a global equilibrium” run with equal cost of intervention. Y1 - 2017 U6 - https://doi.org/10.1002/sdr.1583 VL - 33 IS - 2 SP - 138 EP - 168 ER - TY - CHAP A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakayama, Yuki A1 - Wakui, Tetsuya T1 - Multiobjective Optimal Design of a Gas Turbine Cogeneration Plant by a Revised Hierarchical Optimization Method T2 - ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition N2 - To attain the highest performance of energy supply systems, it is necessary to rationally determine design specifications in consideration of operational strategies corresponding to energy demands. Mixed-integer linear programming (MILP) approaches have been applied widely to such optimal design problems. A MILP method utilizing the hierarchical relationship between design and operation variables have been proposed to solve them efficiently. However, it cannot necessarily be effective to multi-objective optimal design problems because of the existence of a large number of competing design candidates. In this paper, the hierarchical MILP method is revised from the viewpoint of computation efficiency so that it can be applied practically to multi-objective optimal design problems. At the lower level, the order of the optimal operation problems to be solved is changed based on incumbents obtained previously to increase a lower bound for the optimal value of the combined objective function and reduce the number of the optimal operation problems to be solved. At the upper level, a lower bound for the optimal value of the combined objective function is incorporated into the solution method to reduce the number of the design candidates to be generated. This revised hierarchical MILP method is applied to a multiobjective optimal design of a gas turbine cogeneration plant, and its validity and effectiveness are clarified. Y1 - 2017 U6 - https://doi.org/doi:10.1115/GT2017-64296 VL - 3 SP - 1 EP - 14 ER - TY - JOUR A1 - Dierkes, Thomas T1 - Ist die Umsetzung der Open-Access-Komponente in Allianz-Lizenzverträgen wirklich so kompliziert? JF - ABI Technik N2 - Thomas Dierkes ist promovierter Mathematiker und als Entwickler beim Kooperativen Bibliotheksverbund Berlin-Brandenburg (KOBV) am Zuse-Institut Berlin (ZIB) tätig. Er arbeitet dort an der Entwicklung einer „Datendrehscheibe“ für die Umsetzung der Open-Access-Komponente in Allianz-Lizenzen. Er beantwortet die aktuelle Abi Technikfrage: „Ist die Umsetzung der Open-Access-Komponente in Allianz-Lizenzverträgen wirklich so kompliziert?“ Y1 - 2017 U6 - https://doi.org/10.1515/abitech-2017-0051 VL - 37 IS - 3 SP - 237 ER - TY - CHAP A1 - Gottwald, Robert Lion A1 - Maher, Stephen J. A1 - Shinano, Yuji T1 - Distributed Domain Propagation T2 - 16th International Symposium on Experimental Algorithms (SEA 2017) N2 - Portfolio parallelization is an approach that runs several solver instances in parallel and terminates when one of them succeeds in solving the problem. Despite its simplicity, portfolio parallelization has been shown to perform well for modern mixed-integer programming (MIP) and boolean satisfiability problem (SAT) solvers. Domain propagation has also been shown to be a simple technique in modern MIP and SAT solvers that effectively finds additional domain reductions after the domain of a variable has been reduced. In this paper we introduce distributed domain propagation, a technique that shares bound tightenings across solvers to trigger further domain propagations. We investigate its impact in modern MIP solvers that employ portfolio parallelization. Computational experiments were conducted for two implementations of this parallelization approach. While both share global variable bounds and solutions, they communicate differently. In one implementation the communication is performed only at designated points in the solving process and in the other it is performed completely asynchronously. Computational experiments show a positive performance impact of communicating global variable bounds and provide valuable insights in communication strategies for parallel solvers. Y1 - 2017 U6 - https://doi.org/10.4230/LIPIcs.SEA.2017.6 VL - 75 SP - 6:1 EP - 6:11 ER - TY - THES A1 - Clausecker, Robert T1 - Notes on the Construction of Tablebases Y1 - 2017 ER - TY - CHAP A1 - Seblany, Feda A1 - Homberg, Ulrike A1 - Vincens, Eric A1 - Winkler, Paul A1 - Witt, Karl Josef T1 - Merging criteria for the definition of a local pore and the CSD computation of granular materials T2 - Proceedings of the 25th meeting of the Working Group on Internal Erosion in embankment dams and their foundations Y1 - 2017 SN - 978-90-827468-1-5 | 978-90-827468-0-8 SP - 150 EP - 159 PB - Deltares CY - Delft, Netherlands ER - TY - THES A1 - Schweiger, Jonas T1 - Exploiting structure in non-convex quadratic optimization and gas network planning under uncertainty N2 - The amazing success of computational mathematical optimization over the last decades has been driven more by insights into mathematical structures than by the advance of computing technology. In this vein, we address applications, where nonconvexity in the model and uncertainty in the data pose principal difficulties. The first part of the thesis deals with non-convex quadratic programs. Branch&Bound methods for this problem class depend on tight relaxations. We contribute in several ways: First, we establish a new way to handle missing linearization variables in the well-known Reformulation-Linearization-Technique (RLT). This is implemented into the commercial software CPLEX. Second, we study the optimization of a quadratic objective over the standard simplex or a knapsack constraint. These basic structures appear as part of many complex models. Exploiting connections to the maximum clique problem and RLT, we derive new valid inequalities. Using exact and heuristic separation methods, we demonstrate the impact of the new inequalities on the relaxation and the global optimization of these problems. Third, we strengthen the state-of-the-art relaxation for the pooling problem, a well-known non-convex quadratic problem, which is, for example, relevant in the petrochemical industry. We propose a novel relaxation that captures the essential non-convex structure of the problem but is small enough for an in-depth study. We provide a complete inner description in terms of the extreme points as well as an outer description in terms of inequalities defining its convex hull (which is not a polyhedron). We show that the resulting valid convex inequalities significantly strengthen the standard relaxation of the pooling problem. The second part of this thesis focuses on a common challenge in real world applications, namely, the uncertainty entailed in the input data. We study the extension of a gas transport network, e.g., from our project partner Open Grid Europe GmbH. For a single scenario this maps to a challenging non-convex MINLP. As the future transport patterns are highly uncertain, we propose a robust model to best prepare the network operator for an array of scenarios. We develop a custom decomposition approach that makes use of the hierarchical structure of network extensions and the loose coupling between the scenarios. The algorithm used the single-scenario problem as black-box subproblem allowing the generalization of our approach to problems with the same structure. The scenario-expanded version of this problem is out of reach for today's general-purpose MINLP solvers. Yet our approach provides primal and dual bounds for instances with up to 256 scenarios and solves many of them to optimality. Extensive computational studies show the impact of our work. N2 - Der bemerkenswerte Erfolg der angewandten mathematischen Optimierung in den letzten Dekaden ist mehr auf Einsichten in mathematische Strukturen zurückzuführen, als auf eine Steigerung der Rechenleistung. In diesem Sinne adressieren wir Anwendungen, in denen Nichtkonvexität und Unsicherheit in den Daten die Hauptschwierigkeiten darstellen. Der erste Teil dieser Arbeit beschäftigt sich mit nichtkonvexen quadratischen Optimierungsproblemen. Relaxierungen sind integraler Bestandteil von \BranchAndBound{}-Lösungsmethoden für diese Problemkategorie. Wir leisten folgende Beiträge: Erstens beschreiben wir eine neue Art fehlende Linearisierungsvariablen, in der so genannten Reformulation-Linearization-Technique (RLT), zu behandeln. Diese wird inzwischen in der kommerziellen Software CPLEX verwendet. Zweitens beschäftigen wir uns mit der Optimierung einer quadratischen Zielfunktion über die Standardsimplex oder einen so genannten Knapsack-Constraint. Solche grundlegenden Strukturen sind Teil vieler komplexer Modelle. Wir benutzen bekannte Verbindungen zum maximalen Cliquenproblem sowie zu RLT, um neue gültige Ungleichungen herzuleiten, die die Relaxierung verstärken. Drittens beschäftigen wir uns mit dem Pooling Problem, das z.B. in der Erdölindustrie relevant ist. Wie leiten eine neue Relaxierung her, die die wesentliche nicht-konvexe Struktur des Problems erfasst, aber klein genug für eine grundlegende Untersuchung ist. Wir geben eine innere Beschreibung in Form der Extrempunkte, sowie eine äußere Beschreibung in Form von Ungleichungen, die die konvexe Hülle (welche im Allgemeinen kein Polyeder ist) beschreiben, an. Wir zeigen, dass neuen die Ungleichungen die Relaxierung des Pooling Problems erheblich verstärken. Der zweite Teil der Arbeit befasst sich mit einer weiteren Herausforderung in realen Anwendungen, nämlich Unsicherheit in den Eingabedaten. Konkret untersuchen wir die Optimierung des Ausbaus eines Gastransportnetzes, wie z.B. von unserem Projektpartner Open Grid Europe GmbH. Dieses Problem ist bereits bei gegebenen Eingabedaten ein schweres nicht-konvexes gemischt-ganzzahliges Optimierungsproblem. Da zukünftige Nutzungsmuster des Netzes mit großer Unsicherheit behaftet sind, beschreiben wir ein robustes Modell, um den Netzbetreiber gegen verschiedene Szenarien abzusichern. Wir entwickeln einen speziellen Dekompositionsalgorithmus unter Berücksichtigung der hierarchischen Struktur der Ausbauten und der schwachen Kopplung zwischen den Szenarien. Unser Ansatz liefert primale und duale Schranken für Instanzen mit bis zu 256 Szenarien und löst viele beweisbar optimal. Umfangreiche Rechnungen bestätigen die Effizient der vorgestellten Methoden. KW - Nonconvexity KW - Uncertainty KW - Quadratic Programming KW - Relaxations KW - Cutting Planes KW - Standard Quadratic Programming KW - Pooling Problem KW - Gas Network Planning KW - Robust Optimization KW - Decomposition KW - Computations Y1 - 2017 UR - http://dx.doi.org/10.14279/depositonce-6015 ER - TY - CHAP A1 - Müller, Jan A1 - Götschel, Sebastian A1 - Weiser, Martin A1 - Maierhofer, Christiane T1 - Thermografie mit optimierter Anregung für die quantitative Untersuchung von Delaminationen in kohlenstofffaserverstärkten Kunststoffen T2 - NDT.net Proc. DGZfP 2017 N2 - Da kohlenstofffaserverstärkte Kunststoffe (CFK) in anspruchsvollen sicherheitsrelevanten Einsatzgebieten wie im Automobilbau und in der Luftfahrt eingesetzt werden, besteht ein zunehmender Bedarf an zerstörungsfreien Prüfmethoden. Ziel ist die Gewährleistung der Sicherheit und Zuverlässigkeit der eingesetzten Bauteile. Aktive Thermografieverfahren ermöglichen die effiziente Prüfung großer Flächen mit hoher Auflösung in wenigen Arbeitsschritten. Ein wichtiges Teilgebiet der Prüfungen ist die Ortung und Charakterisierung von Delaminationen, die sowohl bereits in der Fertigung als auch während der Nutzung eines Bauteils auftreten können, und dessen strukturelle Integrität schwächen. ;In diesem Beitrag werden CFK-Strukturen mit künstlichen und natürlichen Delaminationen mit Hilfe unterschiedlich zeitlich modulierter Strahlungsquellen experimentell untersucht. Verwendet werden dabei Anregungen mit Blitzlampen und mit frequenzmodulierten Halogenlampen. Mittels Filterfunktionen im Zeit- und Frequenzbereich wird das Kontrast-zu-Rausch-Verhältnis (CNR) der detektierten Fehlstellen optimiert. Verglichen werden anschließend die Nachweisempfindlichkeit, das CNR und die Ortsauflösung der zu charakterisierenden Delaminationen für die unterschiedlichen Anregungs- und Auswertungstechniken. Ergänzt werden die Experimente durch numerische Simulationen des dreidimensionalen Wärmetransportes. Y1 - 2017 ER - TY - THES A1 - Wulkow, Niklas T1 - Modelling the Spread of Innovations by a Markov Process in a Bayesian Framework Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-66869 ER -