- informatik-vortraege - lists.rwth-aachen.de

von Kassing, Jan-Christoph

Dear all, this is a reminder for Michael Schaub's talk with the title "How can algebraic topology help with data analysis?" taking place today (27.06) at 12:30 in the B-IT room 5053.2. Please find the details below --- Abstract --- Topology is concerned with studying properties of spaces that are preserved under continuous transformation. In particular, using notions from topology we can classify spaces according to certain global properties that are invariant under such transformations. While commonly considered a branch of pure mathematics, the use of topological ideas for data analysis has recently seen a surge of interest under the name "Topological Data Analysis". Topological Data Analysis (TDA) is typically concerned with high-dimensional point cloud data. TDA aims to extract the "global shape" of this point cloud using computational tools, such as persistent homology, which aim to extract a global topological description of the point cloud. Stated differently, the whole dataset is treated as a single object, which we aim to characterize. This view contrasts somewhat with the standard perspective of unsupervised learning in which the objects of interest are the points (feature vectors of different objects) themselves, and we are interested in characterizing these objects relative to each other. In this talk, we will provide a brief introduction to topological data analysis and its relation to unsupervised machine learning. We will showcase a few methods that aim to bridge the gap between these two seemingly different viewpoints, and discuss open directions and challenges in this context. ---------------- Part of the programme of the research training group UnRAVeL is a series of lectures on the topics of UnRAVeL’s research thrusts algorithms and complexity, verification, logic and languages, and their application scenarios. Each lecture is given by one of the researchers involved in UnRAVeL. This years topic is "UnRAVeL - New Ideas!". In these lectures, UnRAVeL professors will discuss current research as well as highlight open problems and offer a perspective on potential future directions. All interested doctoral researchers and master students are invited to attend the UnRAVeL lecture series 2024 and engage in discussions with researchers and doctoral students. We are looking forward to seeing you at the lectures. Kind regards, Jan-Christoph for the organisation committee

5 Tage, 23 Stunden

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Einladung Informatik-Oberseminar Dr. Simon Völker, 26. Juni 2024, 13:00 Uhr

von Völker, Simon

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Mittwoch, 26. Juni 2024, 13:00 Uhr Ort: Raum 9222, E3, Informatikzentrum Referent: Dr. Simon Völker Lehrstuhl Informatik 10, Studiencenter Informatik Thema: Beyond Touch: Enriching the Interaction with Mobile Devices Abstract: Mobile devices like smartphones and tablets are now the most common digital tools in daily life, aiding in both work and personal tasks. Much of their success stems from their intuitive touchscreen interaction, which allows users to engage with any digital content by simply touching the screen. However, despite their success, touch input has several limitations and drawbacks. It reduces the extensive input capabilities of our hands to mostly a single touchpoint on a 2D surface, lacking additional information such as the force or orientation of the touch, or extra keys like the multiple modifier buttons found on a mouse or keyboard. These limitations slow down interaction and present numerous challenges, negatively affecting usability. Additional issues such as the fat-finger problem and limited reachability further add to the inconveniences. While the input capabilities are sufficient for simple applications, more complex tasks requiring intensive or intricate input, such as large-scale text editing, are still cumbersome and often avoided. In this thesis, I aim to present several approaches that explore, design, prototype, and analyze new techniques to enrich and expand the limited interaction methods on mobile devices. The goal is to empower users to utilize their movement and sensing capabilities in a more meaningful way, beyond simply creating basic touch input on a sheet of glass. I achieve this by focusing on three approaches: 1) Improving touch input on the device itself by incorporating additional properties of the user's hand, such as the force of a touchpoint. I utilize this additional input dimension to create new interaction techniques and to address existing issues, such as the reachability on a device or the lack of shortcuts on touchscreens. 2) Combining touch with other input methods, such as the user's head or eye movements, to overcome the inherent limitations of touch input. 3) Utilizing the sensing capabilities of mobile devices to detect their surroundings to enable other objects around the device to serve as additional input devices that enable new use cases for mobile devices. My habilitation thesis thus contributes a series of new interaction techniques, implemented and evaluated in lab experiments and user studies, that use touch force sensing, head and gaze input, and objects in the surrounding environment, to make mobile touch input more expressive and effective. Es laden ein: die Dozentinnen und Dozenten der Informatik

1 Woche, 6 Tage

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Einladung: Informatik-Oberseminar Andrea Bönsch

von Office VR

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Mittwoch, 26. Juni 2024, 10.00 Uhr Ort: Seminarraum 003, IT Center, Kopernikusstraße 6 Referentin: Andrea Bönsch, M.Sc. Lehr- und Forschungsgebiet Virtuelle Realität und Immersive Visualisierung (LuFG i12) und IT Center Thema: Social Wayfinding Strategies to Explore Immersive Virtual Environments Abstract: To create Immersive Virtual Environments (IVEs) representing believable and appealing urban spaces, high-quality architectural reconstructions alone are insufficient. Instead, these reconstructions need to be complemented by embedding Virtual Agents (VAs). These computer-controlled, anthropomorphic characters breathe life into the scene, either by actively functioning as direct interaction partners or by passively enlivening the IVEs, e.g., as virtual pedestrians. Regardless of the VAs' roles, user engagement in unfamiliar IVEs primarily revolves around scene exploration to facilitate successful navigation and interaction within the scene. The involved wayfinding procedure --- encompassing users' understanding of their surroundings, route planning, and informed decision-making --- is profoundly grounded in a social context where the presence and behavior of others, in our case, the embedded VAs, influence the user. The core contribution of this thesis is, thus, to enhance our understanding of wayfinding as a social activity in Virtual Reality (VR) applications. We achieved this through the optimization of user support during scene exploration by strategically integrating VAs as inherent components within IVEs. Thereby, we undertake a three-fold approach: Firstly, by adopting a theoretical approach we develop a user-centered wayfinding taxonomy categorizing diverse wayfinding strategies in VR. Within this taxonomy, we introduce VAs as novel wayfinding support, distinguishing between strong social wayfinding (direct guidance by VAs) and weak social wayfinding (subtle VA influence on navigation decisions). This conceptual framework facilitates a deeper understanding of how users interact within IVEs. Secondly, we enhance the spatial behavior of VAs for improved user experience during collaborative navigation. Through ecologically valid VR-based user studies, we uncover nuanced user preferences regarding VA proximity management, behavior during non-interaction periods, and responses to inferred user intents. These findings inform the enhancement of VAs' interactive capabilities displaying responsive and socially compliant behavior for an improved user experience. Lastly, we enable the efficient utilization of VAs as social wayfinding support. Through VR-based user studies, we refine the behavioral design of virtual guides by effectively balancing guidance and the user's autonomous exploration, fostering optimal user-agent interaction during strong social wayfinding. Additionally, we propose a VA design as weak social wayfinding that subtly influences user navigation within IVEs by shaping pedestrian flows, substantiated through empirical validation. Comparative analysis of both approaches in terms of user experience and scene knowledge gain elevates our comprehension of effective VA utilization in immersive environments. In summation, this research contributes to the advancement of VAs as advanced human interfaces, fostering enhanced user acceptance, usability, and perceived social presence within VR environments. Es laden ein: die Dozentinnen und Dozenten der Informatik -- Aleksandra Lukic RWTH Aachen University - Visual Computing Institute - Virtual Reality & Immersive Visualization - Computer Science Department LuFG i12 - IT Center - Computational Science & Engineering Kopernikusstraße 6, 52074 Aachen, Germany Phone +49 241 80-29233 Email office(a)vr.rwth-aachen.de URL www.vr.rwth-aachen.de

2 Wochen, 4 Tage

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UnRAVeL Survey Lecture - Today!

von Kassing, Jan-Christoph

Dear all, this is a reminder for Christina Büsing's talk with the title "Robust Optimization in Health Care" taking place today (13.06) at 12:30 in the B-IT room 5053.2. Please find the details below --- Abstract --- Health is one of the most important factors for the prosperity and well-being of a society. In recent years, this system is challenged by demographic changes: the elderly population (age 65 and older) will increase, which will result in a higher demand for health care services. Simultaneously the decrease in the fertility rate results in a shrinking number of trained medical staff. In order to keep the high standard of the German health care system, it is crucial to improve on the efficient and effective use of our resources. Planning and organization in these fields are complicated by the uncertain nature of health care processes, e.g., the fluctuating demand, arrival time of patients, emergency patients, durations of a single treatment, length of stay or resource failures. These uncertainties are rarely incorporated in the optimization process, if optimization and mathematical methods are used at all. In this talk, I will present, how we approach such kind of optimization problems and show examples how robust optimization can be used to integrated these uncertainties into the optimization process. ---------------- Part of the programme of the research training group UnRAVeL is a series of lectures on the topics of UnRAVeL’s research thrusts algorithms and complexity, verification, logic and languages, and their application scenarios. Each lecture is given by one of the researchers involved in UnRAVeL. This years topic is "UnRAVeL - New Ideas!". In these lectures, UnRAVeL professors will discuss current research as well as highlight open problems and offer a perspective on potential future directions. All interested doctoral researchers and master students are invited to attend the UnRAVeL lecture series 2024 and engage in discussions with researchers and doctoral students. We are looking forward to seeing you at the lectures. Kind regards, Jan-Christoph for the organisation committee

2 Wochen, 6 Tage

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Einladung: Informatik-Kolloquium Herr Prof. Dr. Michael Thielscher

von Maaßen, Leany

+********************************************************************** * * * Einladung * * * * Informatik-Kolloquium * * * +********************************************************************** Prof. Dr. Michael Thielscher, University of New South Wales, Sydney Time: Tuesday, June 18, 2024 at 16:00h Place: E3 Rm 9222 Title: Epistemic Reasoning and Planning for AI Systems with General Intelligence Abstract: AI systems exhibit general intelligence when they are capable of understanding new problems and tasks and can solve them without human intervention. In this talk I, will explain the role of epistemic reasoning and planning to increase the range of problems that an AI system can solve when interacting with other AI agents or humans. I will present a simple high-level action description language for multi-agent epistemic planning along with a more expressive language for describing so-called epistemic games to a general problem-solving system. I will discuss how general problem-solving systems can take advantage of Epistemic Strategy Logic (SLK) as a rich formalism for reasoning about multi-agent systems and the strategic behavior of agents with partial observability, and I will touch upon a new project where we apply epistemic reasoning to create digitally embodied AI companions to address the challenge of reducing loneliness. Short Bio: Michael Thielscher is a professor of computer science at UNSW Sydney, where he is also associated with the iCinema Research Centre. He received his Ph.D. and Higher Doctorate (Habilitation) in Computer Science from Darmstadt University in Germany. He has held the positions of associate professor at Dresden University and visiting professor at Toulouse 1 Capitole University. His Habilitation thesis was honoured with the Award for Research Excellence by the alumni of Darmstadt University; he co-authored the system Fluxplayer, the 2006 World Champion at the AAAI General Game Playing Competition; and in 2009 he won a Future Fellowship Award from the Australian Research Council. His research focuses mainly on general problem-solving AI, the foundations of knowledge representation, and the application of knowledge representation and reasoning both to robotics as well as in arts and culture. 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

3 Wochen, 5 Tage

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Einladung Informatik-Oberseminar Christian Herold, 12. Juni 2024,

von Stephanie Jansen

********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * *********************************************************************** Zeit: Mittwoch, 12. Juni 2024, 09:30 Uhr Ort: Raum 9222, E3, Informatikzentrum Zoom:https://rwth.zoom-x.de/j/68743953886?pwd=HMUlqnO8qakacCpfazBAzKy8b222EK.1 Meeting-ID: 687 4395 3886 Kenncode: 183143 Referent: Christian Herold, M.Sc.; Lehrstuhl Informatik 6 Thema: Context-Aware Neural Machine Translation Abstract: Despite the known limitations, most automatic machine translation (MT) systems today still operate on the sentence-level, ignoring cross-sentence context information. This is, because considering cross-sentence context leads to (i) exponentially increasing complexity, (ii) limits us in terms of the available training data, and (iii) sometimes even reduces translation quality on general MT benchmarks. In this talk, we discuss our efforts to combat these issues and to improve context-aware MT systems. First, we discuss the different decoding strategies for document-level MT and explain how constraining the model attention can result in a more efficient translation system. Second, to tackle the problem of scarce document-level training data, we elaborate on our efforts to utilize monolingual document-level data for MT. Finally, we discuss our efforts on data filtering for MT, which can benefit both sentence- and document-level systems. Es laden ein: die Dozentinnen und Dozenten der Informatik -- Stephanie Jansen Faculty of Mathematics, Computer Science and Natural Sciences Chair of Computer Science 6 ML - Machine Learning and Reasoning RWTH Aachen University Theaterstraße 35-39 D-52062 Aachen Tel: +49 241 80-21601 sek(a)ml.rwth-aachen.de www.hltpr.rwth-aachen.de

1 Monat

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Einladung: Informatik-Oberseminar Sabarinath Mahadevan

von Mahadevan, Sabarinath

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Freitag, 24. Mai 2024, 10.30 Uhr Ort: Raum 025, Mies-van-der-Rohe Str. 15 (UMIC Gebäude) Der Vortrag findet hybrid statt. Zoom: https://rwth.zoom-x.de/j/64536789621?pwd=d2I5Y1VDM2xscVVDbTF0ZnJVWUUvZz09 Meeting ID: 645 3678 9621, Passcode: 998171 Referent: Sabarinath Mahadevan, M.Sc. Lehrstuhl Informatik 13 Thema: The Many Facets of Object Segmentation in Images and Videos Abstract: Segmentation is an important task in computer vision where the pixels belonging to a region of interest, that often share similar characteristics, have to be separated out, and assigned a unique label. This task is relevant in both the image and video domains, and finds direct applications in a wide range of fields including but not limited to autonomous driving, robotics, image editing, and surveillance. For both images and videos, the task of segmentation has various flavours that are often highly related and equally challenging. With the advent of deep learning, modern computer vision algorithms are able to leverage large amounts of available data to achieve impressive performance for many of these segmentation problems. However, such algorithms are often catered either towards segmenting a pre-defined set of object categories, or to some specific sub-domains, and require to be adapted for out-of-domain tasks by training these methods on additional domain-specific data, that is expensive to annotate. As a result, we need algorithms that generalise well to data from unseen domains and also to new task settings in addition to having methods that can efficiently annotate data. The first part of this thesis focusses on efficiently annotating objects using Interactive Segmentation, where the goal is to segment and refine objects in an image using user clicks. Here, I'll present two of our research works that advances the state-of-the-art in the interactive segmentation domain. The first among these, ITIS, develops a novel iterative training strategy in which clicks are added iteratively during training based on the error regions in the network predictions. The iterative training strategy aligns the simulated user-click patterns that are used during training with the actual click patterns that the network would encounter at test time. While this strategy is effective in reducing the number of clicks required to annotate objects, ITIS can only segment one object at a time due to the limitations of its network architecture. We address this problem in our subsequent work called DynaMITe, where we formulate user clicks as spatiotemporal sequences, and develop a novel Transformer based formulation that can process such a sequence and encode them into relevant object or region descriptors. These descriptors are then used to generate the relevant instance segmentation masks. Unlike previous methods, our architecture can process clicks for multiple objects at once, and correspondingly predicts non overlapping segmentation masks without any post-processing. In the second part of this talk, I'll focus on end-to-end video segmentation networks based on 3D convolutions, and present our work STEm-Seg. STEm-Seg is a a bottom-up end-to-end approach for instance segmentation on videos, which uses a partially 3D network to learn spatio-temporal embeddings that can be clustered into instance tubes based on the predicted clustering parameters. Our method is very generic and can be applied to a wide range of instance segmentation tasks in videos. Finally, I’ll present our latest work, Point-VOS, where we show that video segmentation models can learn from spatiotemporally sparse point annotations instead of dense per-object mask annotations. We also present an efficient point-wise annotations scheme, and use it to annotate two large-scale video datasets with associated language expressions. We also present a new Point-VOS benchmark and the corresponding baselines, and show that on our point annotations can be used to achieve results close to state-of-the-art models that use dense mask supervision. Additionally, we evaluate models that connect vision and language on the VNG task, and correspondingly show that our data helps in improving their performance.

1 Monat, 1 Woche

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UnRAVeL Survey Lecture - Today!

von Kassing, Jan-Christoph

Dear all, this is a reminder for Martin Grohe's talk with the title "The Complexity of Constraint Satisfaction" taking place today (16.05) at 12:30 in the B-IT room 5053.2. Please find the details below --- Abstract --- The objective of a constraint satisfaction problem (CSP) is to assign values to variables subject to constraints on the values. Obviously, this is a very general type of problem, and it is not surprising that many algorithmic problems in various application domains can be described as CSPs. It is neither surprising that, in general, CSPs are computationally hard. Considerable efforts have been made to precisely understand the complexity of CSPs, with the goal of identifying tractable restrictions and, ultimately, determining the boundary between tractable and intractable CSPs. A deep theory based on methods from logic, combinatorics, and universal algebra has evolved around these questions. In this survey talk, I will give an overview of the main results and techniques of this theory, and I will highlight some current research topics and open questions. ---------------- Part of the programme of the research training group UnRAVeL is a series of lectures on the topics of UnRAVeL’s research thrusts algorithms and complexity, verification, logic and languages, and their application scenarios. Each lecture is given by one of the researchers involved in UnRAVeL. This years topic is "UnRAVeL - New Ideas!". In these lectures, UnRAVeL professors will discuss current research as well as highlight open problems and offer a perspective on potential future directions. All interested doctoral researchers and master students are invited to attend the UnRAVeL lecture series 2024 and engage in discussions with researchers and doctoral students. We are looking forward to seeing you at the lectures. Kind regards, Jan-Christoph for the organisation committee

1 Monat, 2 Wochen

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Einladung: Informatik-Oberseminar Barna Zajzon

von Abigail Morrison

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: 08.05.2024 um 09:00 Ort: Informatikzentrum, Raum 9222 in E3 Referent: Barna Zajzon, M.Sc. Lehrstuhl Informatik 3 Thema: Sequential information processing in modular spiking networks Abstract: Established paradigms formulate many cognitive processes in terms that involve the manipulation of sequentially organized time-discrete (symbolic) representations. This underscores two basic functional requirements that cortical circuits must fulfill: the ability to create suitable representations from a highly volatile and noisy environment; and the capacity to process, and learn from, their spatio-temporal structure. Combining software tools, simulation studies and theoretical analysis, this thesis entails a series of research projects with the shared goal of disentangling how modular structures enable neural circuits to learn and process sequential information in an efficient and reliable manner. The first part analyses the characteristics of state representations in modular spiking networks and the architectural and dynamical constraints that influence the system's ability to retain, transfer and integrate stimulus information in the presence of noise. It explores the novel hypothesis that modular topographic maps, a pervasive anatomical feature of the cortex, may provide a structural scaffold for sequential denoising of stimulus representations. The second part of this work is dedicated to investigating existing, biologically detailed models of sequence processing. If we are to harvest the knowledge within these models and arrive at a deeper mechanistic understanding of the involved phenomena, it is critical that the models and their findings are accessible, reproducible, and quantitatively comparable. We illustrate these aspects through a replication study and then lay the initial steps towards a conceptual and practical, theoretically-grounded framework for benchmarking and comparison of biophysical sequence learning models. Es laden ein: die Dozentinnen und Dozenten der Informatik -- Prof. Dr. Abigail Morrison Institute for Advanced SImulation (IAS-6) Jülich Research Center & Computer Science 3 - Software Engineering RWTH Aachen http://www.fz-juelich.de/inm/inm-6 http://www.se-rwth.de Office: +49 2428 8097504 Fax # : +49 2461 61-9460 Pronouns: she/her ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Jülich GmbH 52425 Jülich Sitz der Gesellschaft: Jülich Eingetragen im Handelsregister des Amtsgerichts Düren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Stefan Müller Geschäftsführung: Prof. Dr. Astrid Lambrecht (Vorsitzende), Karsten Beneke (stellv. Vorsitzender), Dr. Ir. Pieter Jansens ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

1 Monat, 3 Wochen

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UnRAVeL Survey Lecture - Today!

von Kassing, Jan-Christoph

Dear all, this is a reminder for Jürgen Giesl's talk with the title "Termination and Complexity Analysis of (Probabilistic) Programs: Results and Future Work" taking place today at 12:30 in the B-IT room 5053.2. Please find the details below --- Abstract --- We give an overview on our work on developing techniques for automated termination and complexity analysis for different kinds of programs. While automated tools for the analysis of non-probabilistic programs are already very powerful, we will indicate several research problems that have to be solved in order to obtain techniques of similar power for probabilistic programs. ---------------- Part of the programme of the research training group UnRAVeL is a series of lectures on the topics of UnRAVeL’s research thrusts algorithms and complexity, verification, logic and languages, and their application scenarios. Each lecture is given by one of the researchers involved in UnRAVeL. This years topic is "UnRAVeL - New Ideas!". In these lectures, UnRAVeL professors will discuss current research as well as highlight open problems and offer a perspective on potential future directions. All interested doctoral researchers and master students are invited to attend the UnRAVeL lecture series 2024 and engage in discussions with researchers and doctoral students. We are looking forward to seeing you at the lectures. Kind regards, Jan-Christoph for the organisation committee

2 Monate

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