965 zoekresultaten voor “ssh liacs” in de Publieke website
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Gorlaeus GebouwEinsteinweg 55, Leiden
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DNA expressions - A formal notation for DNA
Promotores: J.N. Kok, H.J. Hoogeboom
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Algorithms for the description of molecular sequences
Promotor: J.N. Kok, P.E. Slagboom Co-promotor: J.F.J. Laros
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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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Estimation and Optimization of the Performance of Polyhedral Process Networks
Promotor: Prof.dr.ir. E. Deprettere
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Instituten
De Universiteit Leiden heeft onderzoeksinstituten gevestigd in Leiden en Den Haag.
- Robots & Religie
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Data science for tax administration
In this PhD-thesis several new and existing data science application are described that are particularly focused on applications for tax administrations.
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Criminaliteit voorspellen in forumnetwerken op het dark web
In dit project gebruiken we sociale netwerkanalyse om het gedrag van gebruikers op online fora en bijbehorende marktplaatsen in de tijd te analyseren.
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From pixels to patterns: AI-driven image analysis in multiple domains
This thesis investigates the application of deep learning techniques in image analysis across various domains, focusing on four main themes: feature extraction, classification, segmentation, and integration, demonstrating the transformative potential of these technologies.
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Matchmaking for open innovation: perspectives on multi-sided markets
Promotores: Prof.dr. B.R. Katzy, Prof.dr. K. Sailer (Munich University)
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Scheduled protocol programming
With the advent of multicore processors and data centers, computer hardware has become increasingly parallel, allowing one to run multiple pieces of software at the same time on different machines. Coordination of these pieces is best expressed in a coordination language as an explicit interaction protocol…
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Multi-dimensional feature and data mining
In this thesis we explore machine and deep learning approaches that address keychallenges in high dimensional problem areas and also in improving accuracy in wellknown problems. In high dimensional contexts, we have focused on computational fluid dynamics (CFD) simulations.
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Multi-Objective Bayesian Global Optimization for Continuous Problems and Applications
A common method to solve expensive function evaluation problem is using Bayesian Global Optimization, instead of Evolutionary Algorithms.
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Computational optimisation of optical projection tomography for 3D image analysis
Optical projection tomography (OPT) is a tomographic 3D imaging technique used for specimens in the millimetre scale.
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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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Governance of Innovation Project Management: Necessary and Neglected
Promotor: Prof.dr. B.R. Katzy, Prof.dr. J. de Vries
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On the Power Efficiency, Low latency, and Quality of Service in Network-on-Chip
In multi/many-core System-on-Chips (SoCs), the performance is almost linearly scaling with the number of processing elements.
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Algorithms for analyzing and mining real-world graphs
Promotor: Prof.dr. J.N. Kok, Co-Promotor: W.A. Kosters
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creatIef, Creatiever, creaTiefst? Onderzoek naar het belang en de werking van creativiteitstraining bij Bachelor ICT-studenten
This dissertation presents the results of the importance of creativity for ICT-students of Dutch universities of applied sciences (in Dutch: hogescholen), and the functioning of training courses that aim to promote creative abilities is highlighted.
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Transdisciplinary Perspectives on Validity: Bridging the Gap Between Design and Implementation for Technology-Enhanced Learning Systems
Technologies that help to enhance our educational environments can be found everywhere.
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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…
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Emergence of Linguistic Universals in Neural Agents via Artificial Language Learning and Communication
Human language is constantly evolving with its linguistic structure being shaped by language users at both individual and population levels. Focusing on the interplay between processes of language acquisition and communicative need in shaping human languages, this thesis introduces a novel computational…
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Learning in Automated Negotiation
This dissertation advances automated negotiation by developing agents that can learn and adapt across diverse negotiation settings through three increasingly sophisticated approaches: automated algorithm configuration, portfolio-based strategy selection, and end-to-end reinforcement learning with graph…
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Contact
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SAILS Lunch Time Seminar: Josette Daemen
Lezing
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SAILS Lunch Time Seminar: Friso Selten
Lezing
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Open-world Continual Learning via Knowledge Transfer
This thesis investigates Open-world Continual Learning (OWCL), a learning paradigm designed for intelligent systems operating in non-stationary environments with persistent exposure to unknown data.
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Faster X-ray Computed Tomography in Real-World Dynamic Applications
This dissertation investigates how the efficiency of Computed Tomography (CT) can be improved for dynamic scientific and industrial applications.
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Latency, Energy, and Schedulability of Real-Time Embedded Systems
Systems are called real-time systems, if the correctness of the system does not only depend on the correctness of the system output but also on whether the output is delivered on time.
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Experience Day Data Science & Artificial Intelligence
Studievoorlichting
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SAILS Lunch Time Seminar: Qinyu Chen
Lezing
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Shape Analysis for Phenotype Characterisation from High-throughput Imaging
We have studied shape with a particular focus on the zebrafish model system. The shape is an essential appearance of the phenotype of a biological specimen and it can be used to read out a current state or response or to study gene expression.
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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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Stressless met behulp van Virtual Reality
Tijdens dit project wordt een app over stress ontwikkeld en geëvalueerd. De app heeft drie functies: een informerende, preventieve en herstellende/curatieve functie.
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Artificial Intelligence, Games and Education
Video games have emerged as one of the most interesting media of the turn of the century. The peculiar characteristic of video games is the biunivocal interaction between the computer and the human player.
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Healthcare Information System Engineering: AI Technologies and Open Source Approaches
Healthcare Information Systems (HIS) are essential for modern healthcare delivery, yet their development faces significant challenges including heterogeneous data formats, regulatory compliance, and the growing demand for AI-driven decision support.
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Data-Driven Machine Learning and Optimization Pipelines for Real- World Applications
Machine Learning is becoming a more and more substantial technology for industry.
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Multi-objective mixed-integer evolutionary algorithms for building spatial design
Multi-objective evolutionary computation aims to find high quality (Pareto optimal) solutions that represent the trade-off between multiple objectives.
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Advancing Learned Algorithms for 2D X-ray Computed Tomography
This thesis surveys the intersection of computed tomography (CT) and machine learning (ML), treating CT as an ill-posed inverse problem shaped by object properties, imaging physics, and data limitations.
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Hybride intelligentie Centrum
Hybride intelligentie (HI) is de combinatie van menselijke en machinale intelligentie, waarbij het menselijk intellect wordt uitgebreid in plaats van vervangen. HI houdt rekening met de menselijke expertise en intentionaliteit bij het nemen van zinvolle beslissingen en het uitvoeren van passende acties,…
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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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Sterrewacht Leiden
Sterrewacht Leiden is het sterrenkundig instituut van de Faculteit der Wiskunde en Natuurwetenschappen van de Universiteit Leiden.
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Combining monitoring with run-time assertion checking
Promotor: F.S. de Boer, Co-promotor: M.M. Bonsangue
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Cyber-Security-by-Integrated-Design (C-SIDe) project
Cyberaanvallen, privacygerelateerde problemen of storingen in het functioneren: veel technologieën die dagelijks worden gebruikt, kennen beveiligingsproblemen die worden opgelost als de software al in gebruik is. Een interdisciplinair project, waarin Olga Gadyatskaya, Harry Wijshoff, Alex Uta en Kristian…
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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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Trustworthy anomaly detection for smart manufacturing
This dissertation explores how we can make anomaly detection—identifying unusual or faulty behavior in complex systems—more trustworthy and effective, with a focus on smart manufacturing.
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Multi-objective Evolutionary Algorithms for Optimal Scheduling
Multi-criteria optimalisatie is een effectieve techniek voor het vinden van optimale oplossingen die een afweging bieden tussen verschillende, tegenstrijdige criteria. Het heeft zijn toepassing gevonden in de wereld om ons heen omdat bij het oplossen van praktische, re¨ele wereld problemen men gewoonlijk…
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Utopia: Universal Three-dimensiOnal Passport for process Individualization in Agriculture
Vroege opsporing van gezondheidsrisico's Landbouwvoedingsmiddelen variëren van nature in hun gedetailleerde interne structuur. Om de vroege opsporing van gezondheidsrisico's als gevolg van besmetting of ziekten te vergemakkelijken, de rijpheid te voorspellen en de verspilling te minimaliseren, is het…
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Planning
Het Gorlaeus Gebouw wordt in drie fasen gerealiseerd. Het nieuwe gebouw is medio 2028 helemaal gereed.