1,004 zoekresultaten voor “liacs” in de Publieke website
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Exploring graph-based clustering and outlier detection algorithms
In the era of big data, extracting insights from complex datasets is a key challenge. This thesis demonstrates the superiority of graph-based methods over traditional clustering (e.g., k-means, DBSCAN) and outlier detection for analyzing high-dimensional and noisy data.
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Reliable and Fair Machine Learning for Risk Assessment
The focus of this thesis is on the technical methods which help promote the movement towards Trustworthy AI, specifically within the Inspectorate of the Netherlands.
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Knowledge discovery from patient forums: gaining novel medical insights from patient experiences
Patients share valuable advice and experiences with their peers in online patient discussion groups.
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Data structures for quantum circuit verification and how to compare them
Quantum computers are a proposed fundamentally new type of computer. They aim to perform some computations much faster than previously possible by exploiting phenomena at the quantum scale, called superposition and entanglement.
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LABDA (Learning Network for Advanced Behavioural Data Analysis)
Onderzoeken hoe gegevens afkomstig van draagbare technologieën kunnen worden gebruikt om effectieve gedragsveranderingen te identificeren die hopelijk zullen leiden tot gezondheidsverbeteringen.
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Experience Day Data Science & Artificial Intelligence
Studievoorlichting
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SAILS Lunch Time Seminar: Tom Kouwenhoven
Lezing
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Over de faculteit
De faculteit biedt een internationale academische omgeving met 36% van de studenten, promovendi en onderzoekers uit het buitenland.
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Systemen en beveiliging
Onderzoekers van LIACS werken aan het bedenken van de computers van morgen die de ruggengraat zullen vormen van de Cloud en Edge computing paradigma’s en ‘the Internet of Things’. In dit verband zijn we betrokken bij onderzoek en ontwikkeling van high performance computing systemen, embedded & real-time…
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Computed fingertip touch for the instrumental control of musical sound with an excursion on the computed retinal afterimage
Promotor: Prof.dr. S. Haring
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Exploring Images With Deep Learning for Classification, Retrieval and Synthesis
In 2018, the number of mobile phone users will reach about 4.9 billion. Assuming an average of 5 photos taken per day using the built-in cameras would result in about 9 trillion photos annually.
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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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Massively collaborative machine learning
Promotor: J. N. Kok, Co-promotor: A. J. Knobbe
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Deep learning for visual understanding
With the dramatic growth of the image data on the web, there is an increasing demand of the algorithms capable of understanding the visual information automatically.
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From Benchmarking Optimization Heuristics to Dynamic Algorithm Configuration
For optimization problems, it is often unclear how to choose the most appropriate optimization algorithm. As such, rigorous benchmarking practices are critical to ensure we can gain as much insight into the strengths and weaknesses of these types of algorithms.
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Robust rules for prediction and description.
In this work, we attempt to answer the question:
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Enhanced coinduction
Promotores: Prof.dr. F.S. de Boer, Prof.dr. J.J.M.M. Rutten (Radboud Universiteit Nijmegen)
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Who gets what, when, and how? An analysis of stakeholder interests and conflicts in and around Big Science
Big Science, commonly defined as conventional science made big in three dimensions, namely organizations, machines, and politics, brings a plethora of different stakeholders together, often for a long period of time. This includes policymakers, scientists, (scientific) managers as well as local “host”…
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Interactive scalable condensation of reverse engineered UML class diagrams for software comprehension
Promotores: Prof.dr. J.N. Kok, Prof.dr. M.R.V. Chaudron (Chalmers Univ., Sweden)
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Calculated Moves: Generating Air Combat Behaviour
By training with virtual opponents known as computer generated forces (CGFs), trainee fighter pilots can build the experience necessary for air combat operations, at a fraction of the cost of training with real aircraft.
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Business incubators: the impact of their support
A New Technology-Based Firm (NTBF) is a significant enabler of job creation and a driver of the economy through stimulating innovation.
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Opinion Diversity through Hybrid Intelligence
This dissertation explores how Large Language Models (LLMs) can effectively and responsibly contribute to complex decision-making processes. By combining AI and human intelligence, Hybrid Intelligence (HI) emerges, allowing the strengths of both humans and machines to be utilized.
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Deep Learning Solutions for Domain-Specific Image Segmentation
Image segmentation is a fundamental task in computer vision, with applications ranging from medical diagnostics to archaeological research.
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Image analysis for gene expression based phenotype characterization in yeast cells
Promotores: T.H.W. Bäck, A. Plaat, Co-promotor: F.J. Verbeek
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Arguably augmented reality : relationships between the virtual and the real
This thesis is about augmented reality (AR). AR is commonly considered a technology that integrates virtual images into a user’s view of the real world.
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Fostering Curiosity Through Video Games
This thesis manuscript explores the use of video games as tools for conceptual exploration and academic research.
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Knowledge Extraction from Archives of Natural History Collections
Natural history collections provide invaluable sources for researchers with different disciplinary backgrounds, aspiring to study the geographical distribution of flora and fauna across the globe as well as other evolutionary processes.
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Tailoring x-ray tomography techniques for cultural heritage research
Visualizing the internal structure is a crucial step in acquiring knowledge about the origin, state, and composition of cultural heritage artifacts. Among the most powerful techniques for exposing the interior of cultural heritage objects is computed tomography (CT), a technique that computationally…
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Large scale visual search
Promotor: J.N. Kok, Co-promotor: M.S. Lew
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DnQ - Divide and Quantum
Divide & Quantum (D&Q) biedt verschillende oplossingen om de kracht van quantumcomputers op korte termijn te benutten, en stelt volledige pipelines voor, van theoretisch onderzoek, via implementatie tot real-world case studies in verschillende disciplines, tot wetenschapscommunicatie naar een bredere…
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AI Labs
AI Labs zijn samenwerkingen van de Universiteit Leiden met externe partner zoals bedrijven, overheidsinstellingen en andere universiteit op het gebied van kunstmatige intelligentie. De Faculteit voor Wis-en Natuurkunde is uniek gesitueerd op het grootste Bioscience Park van Nederlands, en ligt direct…
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DSE 2.0
DSE 2.0: Naar een optimaal ontwerp van complexe, gedistribueerde cyber-fysieke systemen
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Designing Ships using Constrained Multi-Objective Efficient Global Optimization
A modern ship design process is subject to a wide variety of constraints such as safety constraints, regulations, and physical constraints.
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Reasoning about object-oriented programs: from classes to interfaces
Throughout the history of computer science, a major challenge has been how to assert that software is free of bugs and works as intended. Software bugs can lead to serious negative impacts on any software system. Throughout the main body of the thesis, we implemented a series of studies on exploring…
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Optimally weighted ensembles of surrogate models for sequential parameter optimization
It is a common technique in global optimization with expensive black-box functions to learn a surrogate-model of the response function from past evaluations and use it to decide on the location of future evaluations.
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Imperfect information variants of combinatorial games
Combinatorial games are games for two competing players, moving in a turn-by-turn fashion, in which there is no chance nor hidden information. Chess, checkers and the simpler tic tac toe are well-known examples of this class of games, as well as game of go.
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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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Cleared for take-off, Game-based learning to prepare airline pilots for critical situations
Over the last decades, aviation safety has improved strongly. As a downside, airline pilots do not have as many opportunities to develop through experience the competencies that they need in critical situations.
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Sociaal ingebedde AI-systemen
Dit interdisciplinair onderzoeksproject verkent verschillende adaptieve machine-learning methoden die inzicht kunnen geven in de interactie tussen mens en machine. Het uiteindelijke doel is een open en natuurlijke communicatie tussen mens en AI die moet resulteren in wederzijds vertrouwen, samenwerking…
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Exploratieve datamining in multimodale gegevens
De verandering van een gesloten instelling naar een open leefomgeving voor patiënten met een laat stadium van dementie zal de patiënten meer vrijheid geven in hun dagelijks leven. Het effect van deze verandering op de mobiliteit van de patiënten, hun activiteiten en hun interactie met anderen zal worden…
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Progressive Indexes
Interactive exploration of large volumes of data is increasingly common, as data scientists attempt to extract interesting information from large opaque data sets. This scenario presents a difficult challenge for traditional database systems, as (1) nothing is known about the query workload in advance,…
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Towards a Relational Approach to Understanding Interactions in Interactive Art
This thesis introduces a relational interaction model and a practical tool for describing, visualising and generating interactive dialogues.
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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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Formal models of software-defined networks
SDN (Software-Defined Networking) represents a revolutionary approach to network architecture that enables the dynamic and flexible management of network resources through software-based control. This dissertation introduces the idea of SDN and its southbound protocol OpenFlow, then presents the formal…
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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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Abstract delta modeling: software product lines and beyond
Promotor: Prof.dr. F.S. de Boer, Co-promotor: D. Clarke
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Multi Modal Representation Learning and Cross-Modal Semantic Matching
Humans perceive the real world through their sensory organs: vision, taste, hearing, smell, and touch. In terms of information, we consider these different modesalso referred to as different channels of information or modals.
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Fuzzy systems and unsupervised computing: exploration of applications in biology
In this thesis we will explore the use of fuzzy systems theory for applications in bioinformatics.
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Studying the Benefits of Using UML on Software Maintenance: an Evidence-Based Approach.
Including modelling as part of software development appears to have various benefits.
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Machine learning and computer vision for urban drainage inspections
Sewer pipes are an essential infrastructure in modern society and their proper operation is important for public health. To keep sewer pipes operational as much as possible, periodical inspections for defects are performed.