informatik-vortraege November 2023

informatik-vortraege@lists.rwth-aachen.de

3 Teilnehmer
4 Diskussionen

Einladung: Informatik-Oberseminar Henri Lotze

von Henri Lotze

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Montag, 13. November 2023, 09.30 Uhr Ort: Informatikzentrum, E3, 2. Etage, Raum 9222 Referent: Henri Lotze M.Sc. Lehr- und Forschungsgebiet Theoretische Informatik Thema: Going Offline -- Delays, Reservations and Predictions in Online Computation Abstract: The study of classical online computation builds upon a rather simple model. The input to a given problem is not known in advance, decisions have to made immediately upon the arrival of a new element and these decisions are irrevocable. While this model is very well suitable to compute worst case bounds to a broad range of problems, there are some problems which are not well suited for this analysis. Naturally, problems that do not admit a constant approximation ratio in their offline formulation do not admit a constant competitive ratio in the worst case in the online formulation. However, some problems that are approximable still do not admit a constant competitive ratio when analyzed in the online case. For a subset of these problems, such as the Online Simple Knapsack problem and the class of general F-Node- and F-Edge-Deletion problems, the reason for this seems to be that a single, specific bad decision by an algorithm can be arbitrarily punished by an adversary. In this talk, we explore modifications of the classical online model with the aim to find natural models that on the one hand cover a large range of problems and on the other hand work against pathological kinds of instances that restrict an algorithm from obtaining a constant competitive ratio. To this end, we study three modifications of the classical online model. The models that we study are that of "Late Accepts" -- with Advice --, which allows to postpone decisions in online minimization problems until a current partial solution does not uphold a certain property anymore. The second one is that of "Reservations", in which any decision may be postponed for a cost proportional to the gain of an item. Finally, the model of "Bounded Predictions" allows an online algorithm to see the complete instance in advance, with a caveat: There is noise on the instance -- controlled by an adversary -- and each element may actually deviate from its prediction, up to factor that is known to the algorithm. We are able to partially classify the advice complexity of the complete class of both F-Node-Deletion and F-Edge-Deletion problems. We give tight bounds on the competitive ratio for the Online Simple Knapsack problem with Reservations for the whole range of possible reservation costs, i.e. for a factor between 0 and 1. Finally, we give partially tight bounds for the Online Simple Knapsack problem with Bounded Predictions for the whole range of possible noise factors on the size of the items. Es laden ein: die Dozentinnen und Dozenten der Informatik

4 Monate, 3 Wochen

Einladung: Informatik-Oberseminar Herr Fabian Ohler

von Maaßen, Leany

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Freitag, 08.12.2023, 13:00-14:00 Uhr Ort: Raum 5053.1 (kleiner B-IT-Hörsaal)/Informatikzentrum, Ahornstraße 55 Referent: Herr Fabian Ohler, M. Sc. Lehrstuhl Informatik 5 Thema: Die Rolle funktionaler Domänenmodelle in der Entwicklung allianzgetriebener Softwareplattformen Abstract: Organisationen können durch die Bildung von Allianzen gemeinsame Ziele verfolgen. Gestalten sie dabei zusammen eine Plattform, müssen bereits in einem frühen Stadium eine Vielzahl an Prozessen zusammengeführt und die Verteilung der Funktionen auf die Akteure geklärt und koordiniert werden. Im Vortrag wird die methodische und technische Unterstützung für die unternehmensübergreifenden, von Kollaboration geprägten Entwurfsaktivitäten der zugehörigen Systemarchitektur am Beispiel einer Plattformentwicklung zur Kooperation öffentlicher Verkehrsträger und Verkehrsverbünde vorgestellt. Dafür wird eine empirisch ausgearbeitete Methode zur Herleitung eines funktionalen Domänenmodells und für die Weiterentwicklung zu einer Systemarchitekturbeschreibung präsentiert. Die Rolle des funktionalen Domänenmodells in diesem Kontext wird beleuchtet. Ergänzend werden Software-Werkzeuge zur Unterstützung der Entwicklungsphasen der Feinspezifikation und Validierung vorgestellt. Diese basieren auf in Experteninterviews erhobenen Erkenntnissen über die Defizite bislang eingesetzter Werkzeuge sowie daraus abgeleiteten Anforderungen. Die erarbeitete Methode wurde bereits erfolgreich in zwei Domänen eingesetzt, so dass eine Übertragbarkeit auf weitere Domänen zu erwarten ist. Es laden ein: die Dozentinnen und Dozenten der Informatik _______________________________ Leany Maaßen RWTH Aachen University Lehrstuhl Informatik 5, LuFG Informatik 5 Prof. Dr. Stefan Decker, Prof. Dr. Matthias Jarke, Prof. Gerhard Lakemeyer Ph.D., JunProf. Dr. Sandra Geisler Ahornstrasse 55 D-52074 Aachen Tel: 0241-80-21509 Fax: 0241-80-22321 E-Mail: maassen(a)dbis.rwth-aachen.de

5 Monate

Einladung: Informatik-Oberseminar Istvan Sarandi

von Sárándi, István

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Dienstag, 5. Dezember 2023, 13.00 Uhr Ort: Großer b-it Raum (5053.2), Geb. E2, Informatikzentrum, Ahornstr. 55 Der Vortrag findet hybrid statt. Zoom: https://rwth.zoom-x.de/j/63672895840?pwd=L2ZoLzRDMzV3dzIrZ2hsNTAwaFNldz09 Meeting ID: 636 7289 5840, Passcode: 964382 Referent: Istvan Sarandi, M.Sc. Lehrstuhl Informatik 13 Thema: Robust and Efficient Methods in Visual 3D Human Pose Estimation Abstract: Computer vision algorithms for perceiving humans in the real world are crucial for several impactful emerging technologies, including self-driving cars and mobile service robots. In this talk, I will present three contributions to improving the state of the art in deep learning-based 3D human pose estimation, that is, localizing major anatomical landmarks of the human body in 3D space from RGB images only. The central themes are robustness and efficiency, which constitute the main challenges in robotics applications. We start by addressing robustness to occlusions, i.e., when objects block the line of sight between the person and the camera. After presenting the first systematic study of how occlusions deteriorate 3D pose estimation accuracy, we propose to mitigate the problem using an effective synthetic occlusion data augmentation strategy. We then turn to the problem of truncation, i.e., when only a part of the body is within the camera's field of view. We develop a truncation-robust heatmap representation, which also allows learned recovery of the metric scale. Building upon this capability, I present an end-to-end learned absolute pose estimation method called MeTRAbs, for robustly reconstructing human poses in the camera's reference frame at state-of-the-art accuracy. In the third part, I present the largest-scale experiment reported in the 3D pose literature to date, by merging a total of 32 datasets, in the pursuit of improved in-the-wild generalization, outside the controlled environments of motion capture studios. We overcome the challenge of differently annotated datasets through a novel affine-combining autoencoder formulation for capturing the common information in different landmark annotation formats. Importantly, these methods can run on low-powered robot hardware in real time. I conclude with a discussion of possible extensions to the presented works, as well as exciting future challenges for the field as a whole. Es laden ein: die Dozentinnen und Dozenten der Informatik

5 Monate

Einladung: Informatik-Oberseminar Jannis Klinkenberg

von Klinkenberg, Jannis

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Freitag, 01. Dezember 2023, 09.00 Uhr Ort: IT Center, Kopernikusstraße 6, Seminarraum 003 Referent: Jannis Klinkenberg M.Sc. Lehrstuhl Informatik 12 Thema: Reactive Runtimes for Parallel Programming Models on Shared, Distributed, and Heterogeneous Memory Systems Abstract: The persistent drive to enhance the scale and precision of scientific simulations over the past decades has created an ever-growing demand for computational resources. This, in turn, has catalyzed several innovations in the architectural design and manufacturing procedures of computer systems, such as the introduction of multi-core processors and multi-socket shared memory systems, which are typically operated in High Performance Computing (HPC) installations. Historically, scientific applications have primarily been developed with the presumption of a uniform execution environment, where every compute node and core within an installation operates at a consistent, unchanging speed and where the execution time can be accurately predicted. However, in the last decades, both hardware and software have become increasingly complex and often exhibit dynamic execution behavior, causing performance fluctuations and run time variability. Consequently, a priori load balancing within and between compute nodes becomes increasingly challenging in such environments. Applications as well as runtime systems therefore demand for new techniques to be able to dynamically react to changing execution conditions and efficiently balance the load. This thesis presents reactive concepts, runtime implementations, and runtime extensions designed to address the growing complexity of both hardware and software. The objective is to provide portable, vendor-independent solutions to improve application performance, minimize run time variability and mitigate impending load imbalances. Locality-aware task scheduling extensions in OpenMP improve the data locality on contemporary shared memory NUMA architectures by dynamically identifying physical data locations and reactively adjusting the task distribution and scheduling. Further, continuous performance introspection combined with reactively migrating or replicating tasks in distributed memory can efficiently detect and mitigate emerging imbalances at execution time. Lastly, abstracting regular memory allocation allows specifying additional requirements or hints regarding how the data is used throughout the execution, which can be exploited to dynamically guide the data placement on systems with heterogeneous memory. Systematic evaluations demonstrate the effectiveness of the presented concepts and show that placing the burden on runtime systems to proficiently handle these low-level aspects is crucial to achieve high performance on current and future architectures. Es laden ein: die Dozentinnen und Dozenten der Informatik

5 Monate, 1 Woche

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informatik-vortraege November 2023