128 zoekresultaten voor “tasks” in de Publieke website
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Strategic Task Forces
Una Europa heeft zes transversale thema’s vastgesteld en ingevoerd als leidende beginselen voor samenwerking. Deze thema’s hebben als doel het personeel en de studenten van Una Europa te helpen deze thema's in concrete acties om te zetten.
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Semi-partitioned Scheduling and Task Migration in Dataflow Networks
Promotor: Ed F. Deprettere, Co-promotor: Todor P. Stefanov
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Coping with administrative tasks: A cross-country analysis from a street-level perspective
This study seeks to analyse how job stress could be the result of performing administrative tasks
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Jorrit Rijpma neemt deel aan het CEPS Task Force European Border and Coast Guard
Op 21 juni sprak Jorrit Rijpma op de eerste bijeenkomst van het Task Force over een Europese Grens- en Kustwacht, opgericht door het Centre for European Policy Studies in Brussel.
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De Brabander en Martens winnen Earli Outstanding Publication Award 2015
Op de tweejaarlijkse conferentie van de European Association for Learning and Instruction (Earli) op Cyprus hebben dr. Kees de Brabander en prof. dr. Rob Martens, beiden - eertijds - verbonden aan de afdeling Onderwijsstudies van het instituut Pedagogische Wetenschappen met hun artikel
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A mobile approach-avoidance task
Promotie
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Visual Relation extraction Based on Deep Cross-media Transfer Network
Building a Deep Cross-media Transfer Network to extract visual relations that relieve the problem of insufficient training data for visual tasks.
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Generalized Strictly Periodic Scheduling Analysis, Resource Optimization, and Implementation of Adaptive Streaming Applications
This thesis focuses on addressing four research problems in designing embedded streaming systems.
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Data Centres for Natural Recources and Products
Creating information portals for support of European environmental policy.
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Improved hard real-time scheduling and transformations for embedded Streaming Applications
This thesis addresses the problem of designing performance and energy efficient embedded streaming systems, that is, systems which process a stream of input data coming from the environment and generate a stream of output data going into the environment.
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Structured Parallel Programming for Monte Carlo Tree Search
The thesis is part of a bigger project, the HEPGAME (High Energy Physics Game). The main objective for HEPGAME is the utilization of AI solutions, particularly by using MCTS for simplification of HEP calculations.
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Spectral imaging and tomographic reconstruction methods for industrial applications
Radiography is an important technique to inspect objects, with applications in airports and hospitals. X-ray imaging is also essential in industry, for instance in food safety checks for the presence of foreign objects.
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Pattern mining for label ranking
Promotor: J.N. Kok, Co-promotor: C.M. Soares, A.J. Knobbe
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Computational speedups and learning separations in quantum machine learning
This thesis investigates the contribution of quantum computers to machine learning, a field called Quantum Machine Learning. Quantum Machine Learning promises innovative perspectives and methods for solving complex problems in machine learning, leveraging the unique capabilities of quantum computers…
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Quantum machine learning: on the design, trainability and noise-robustness of near-term algorithms
This thesis addresses questions on effectively using variational quantum circuits for machine learning tasks.
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Una Europa-gemeenschap in Leiden
De Universiteit Leiden is sinds januari 2023 actief betrokken bij de alliantie.
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Massively collaborative machine learning
Promotor: J. N. Kok, Co-promotor: A. J. Knobbe
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Self-Adjusting Surrogate-Assisted Optimization Techniques for Expensive Constrained Black Box ProblemsBagheri, S.
Optimization tasks in practice have multifaceted challenges as they are often black box, subject to multiple equality and inequality constraints and expensive to evaluate.
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On hard real-time scheduling of cyclo-static dataflow and its application in system-level design
Promoter: Ed F. Deprettere, Co-promoter: Todor P. Stefanov
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Singing is silver, hearing is gold: impacts of local FoxP1 knockdowns on auditory perception and gene expression in female zebra finches
The experiments described in this thesis employ local lentiviral knockdowns in brain areas of female zebra finches followed by behavioural assays consisting of preference and Go/Nogo tasks.
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Voor wetenschappelijk personeel
Una Europa biedt veel verschillende mogelijkheden voor Leidse academici.
- Alumini
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Voor ondersteunend personeel
Una Europa biedt veel mogelijkheden voor ondersteunend personeel.
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Learning from small samples
Learning from small data sets in machine learning is a crucial challenge, especially when dealing with data imbalances and anomaly detection. This thesis delves into the challenges and methodologies of learning from small datasets in machine learning, with a particular focus on addressing data imbalances…
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Learning-based Representations of High-dimensional CAE Models for Automotive Design Optimization
In design optimization problems, engineers typically handcraft design representations based on personal expertise, which leaves a fingerprint of the user experience in the optimization data. Thus, learning this notion of experience as transferrable design features has potential to improve the performance…
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Learning class-imbalanced problems from the perspective of data intrinsic characteristics
The class-imbalance problem is a challenging classification task and is frequently encountered in real-world applications. Various techniques have been developed to improve the imbalanced classification performance theoretically and practically.
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Política, Cuerpo e Identidad
This book aims to be a point of reflection and debate for journalists, academics and students to recognize a fundamental task in the duty of the communications professional, which is to influence through their daily work and their routines in order to achieve a more inclusive and plural society, through…
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Exploring deep learning for multimodal understanding
This thesis mainly focuses on multimodal understanding and Visual Question Answering (VQA) via deep learning methods. For technical contributions, this thesis first focuses on improving multimodal fusion schemes via multi-stage vision-language interactions.
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Imaging polarimetry for the characterisation of exoplanets and protoplanetary discs. Scientific and technical challenges
Promotor: Prof.dr. C.U. Keller
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Information Diffusion Analysis in Online Social Networks based on Deep Representation Learning
With the emergence of online social networks (OSNs), the way people create and share information has changed, which becomes faster and broader than traditional social media.
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Private lessons for guitar and ukelele | English spoken
Kunst en vrije tijd, Kunst en vrije tijd
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Algorithm design for mixed-integer black-box optimization problems with uncertainty
The increasing competition in the automotive industry requires the tailored, swift development of technologically sophisticated vehicles. Therefore, the computationally expensive state-of-the-art simulation technologies are combined with optimization algorithms. An example of a real-world optimization…
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Algorithm selection and configuration for Noisy Intermediate Scale Quantum methods for industrial applications
Quantum hardware comes with a different computing paradigm and new ways to tackle applications. Much effort has to be put into understanding how to leverage this technology to give real-world advantages in areas of interest for industries such as combinatorial optimization or machine learning.
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Aspects of Record Linkage
Promotores: Prof.dr. J.N. Kok, Prof.dr. C.A. Mandemakers, Co-Promotor: G. Bloothooft
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Aspects of the analysis of cell imagery: from shape to understanding
In this thesis, we have studied cell images from two types of cells, including pollen grains and the immune cells, neutrophils. These images are captured using a bright field microscope and a confocal microscope.
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Inducing spin triplet superconductivity in a ferromagnet
Promotor: J. Aarts
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Leukemia treatment & cognitive development
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Deep learning for tomographic reconstruction with limited data
Tomography is a powerful technique to non-destructively determine the interior structure of an object.Usually, a series of projection images (e.g.\ X-ray images) is acquired from a range of different positions.
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Understanding deep meta-learning
The invention of neural networks marks a critical milestone in the pursuit of true artificial intelligence. Despite their impressive performance on various tasks, these networks face limitations in learning efficiently as they are often trained from scratch.
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The power of one qubit in quantum simulation algorithms
Quantum computing is an emerging technology, which holds the potential to simulate complex quantum systems beyond the reach of classical numerical methods.Despite recent formidable advancements in quantum hardware, constructing a quantum computer capable of performing useful calculations remains challenging.In…
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Una Europa
Bouwen aan de universiteit van de toekomst
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A Model Membrane Approach to Elucidate the Molecular Organization in the Skin Barrier
Promotor: J. A. Bouwstra
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Benchmarking Discrete Optimization Heuristics
This thesis involves three topics: benchmarking discrete optimization algorithms, empirical analyses of evolutionary computation, and automatic algorithm configuration.
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Precision modeling of breast cancer in the CRISPR era
The molecular mechanisms that instigate a healthy cell to become malignant are fueled by (epi)genetic alterations in so-called driver genes.
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Cryptography from quantum uncertainty in the presence of quantum side information
Promotor: Ronald Cramer, Co-promotor: Serge Fehr
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Imaging complex model catalysts in action
From surface science towards industrial practice using high-pressure scanning tunneling microscopy.
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Quality-driven multi-objective optimization of software architecture design: method, tool, and application
Promotores: Prof.dr. T.H.W. Bäck, Prof.dr. M.R.V. Chaudron, Co-Promotor: M.T.M. Emmerich
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An Online Corpus of UML design models: Construction and empirical studies
Promotores: J. Kok, M. Chaudron (Chalmers University)
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Synthetic model microswimmers near walls
Synthetic microswimmers take an important place within the interdisciplinary field of active soft matter.
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Automated machine learning for dynamic energy management using time-series data
Time-series forecasting through modelling sequences of temporally dependent observations has many industrial and scientific applications. While machine learning models have been widely used to create time-series forecasting models, creating efficient and performant time-series forecasting models is…