166 zoekresultaten voor “algorithms” in de Publieke website
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Algorithms for finite rings
Promotores: H.W. Lenstra, K. Belabas (University of Bordeaux)
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Efficient and Automatic Tomographic Reconstruction Algorithms
In this thesis we present several methods to automate tomographic reconstruction algorithms and several novel tomographic reconstruction algorithms with the focus on being easily applicable and efficient to use.
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On continued fraction algorithms
Promotor: Robert Tijdeman, Co-promotor: Cornelis Kraaikamp
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Accountable Artificial Intelligence: Holding Algorithms to Account
Artificial intelligence algorithms govern in subtle, yet fundamental ways, the way we live and are transforming our societies. The promise of efficient, low‐cost or ‘neutral’ solutions harnessing the potential of big data has led public bodies to adopt algorithmic systems in the provision of public…
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Algorithm for Structural Variant Detection
Structural variants (SVs) are the hidden architecture of the human genome, and are critical for us to understand diseases, evolution, and so on.
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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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Optimization of quantum algorithms for near-term quantum computers
This thesis covers several aspects of quantum algorithms for near-term quantum computers and its applications to quantum chemistry and material science.
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Network flow algorithms for discrete tomography
Promotor: R. Tijdeman, Co-promotor: H.J.J. te Riele
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Sparsity-Based Algorithms for Inverse Problems
Inverse problems are problems where we want to estimate the values of certain parameters of a system given observations of the system. Such problems occur in several areas of science and engineering. Inverse problems are often ill-posed, which means that the observations of the system do not uniquely…
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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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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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Novel detectors and algorithms for electron nano-crystallography
Promotor: Prof.dr. J.P. Abrahams, Prof.dr. M. van Heel
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Stochastic and Deterministic Algorithms for Continuous Black-Box Optimization
Continuous optimization is never easy: the exact solution is always a luxury demand and the theory of it is not always analytical and elegant.
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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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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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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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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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PhD Candidate, Brain-inspired LLM for Edge Devices: A Hardware-Algorithm Co-design Framework
Wiskunde en Natuurwetenschappen, Leiden Institute of Advanced Computer Science (LIACS)
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Algorithms help improve building design
Modern optimization algorithms offer solutions for architectural decisions like spatial, structural and energy efficiency. A young computer scientist from Leiden University co-authored a paper that won the Best Paper Award at a leading conference in Krakow during the summer.
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Random walks on Arakelov class groups
The main topic of this PhD thesis is the Arakelov ray class group of a number field, an algebraic object that contains both the ideal class group structure and the unit group structure.
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Leidse studenten winnen Benelux Algorithm Programming Contest 2014
Team Syntax Error, met Bas Nieuwenhuizen, Mathijs van de Nes, Niels ten Dijke, alle drie masterstudenten Computer Science, heeft de Benelux Algorithm Programming Contest gewonnen en heeft zich daarmee geplaatst voor de Northwestern European Regional Contest in Zweden, op 29 en 30 november.
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Novel system-inspired model-based quantum machine learning algorithm for prediction and generation of High-Energy Physics data
De huidige en toekomstige quantumcomputers vormen dezelfde uitdaging als de laser in zijn begindagen. In theorie werd voorspeld dat de laser een bron van zeer speciaal, zeer krachtig licht zou zijn. Maar in die tijd waren er geen duidelijke toepassingen voor. Critici van het idee noemden het een probleem…
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DNA expressions - A formal notation for DNA
Promotores: J.N. Kok, H.J. Hoogeboom
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Team ‘Geen Syntax’ van Universiteit Leiden wint Benelux Algorithm Programming Contest 2013
Het Leidse team 'Geen Syntax', bestaande uit Bas Nieuwenhuizen, Mathijs van de Nes en Raymond van Bommel, heeft in Utrecht de Benelux Algorithm Programming Contest (BAPC) 2013 gewonnen. Deze Leidse studenten wiskunde en informatica losten de 10 opgaven een uur sneller op dan alle andere teams.
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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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Deterministic equation solving over finite fields
Promotor: H.W. Lenstra
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Methods to simulate fermions on quantum computers with hardware limitations
This thesis is a collection of theoretical works aiming at adjusting quantum algorithms to the hardware of quantum computers.
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Massively collaborative machine learning
Promotor: J. N. Kok, Co-promotor: A. J. Knobbe
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HEPGAME
HEPGAME is a research project that combines the world’s fastest computer algebra system for High Energy Physics equations, FORM, with insights from artificial intelligence. The name combines High Energy Physics and Games.
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On the computation of norm residue symbols
An algorithm is discussed to compute the exponential representation of principal units in a finite extension field F of the p-adic rationals.
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Special edition Information Polity
In this special edition of Information Polity there is a focus on the transparency challenges of using algorithms in government in decision-making procedures at the macro-, meso-, and micro-levels.
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Meta-heuristics for vehicle routing and inventory routing problems
Promotores: T.H.W. Bäck, Y. Tan, Co-promotor: M.T.M. Emmerich
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Complex multiplication of abelian surfaces
Promotor: Peter Stevenhagen
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Reconstruction Methods for Combined HAADF-STEM and EDS Tomography
The research in this thesis is focused on tomographic reconstruction based on two imaging modalities in electron microscopy.
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Guiding evolutionary search towards innovative solutions
Promotors: Prof.dr. T.H.W. Bäck, Prof.dr. B. Sendhoff (Technische Universität Darmstadt)
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Modular curves, Arakelov theory, algorithmic applications
Promotor: S.J. Edixhoven, Co-promotor: R.S. de Jong
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The Many Faces Of Online Learning
In this dissertation several settings in the Online Learning framework are studied. The first chapter serves as an introduction to the relevant settings in Online Learning and in the subsequent chapters new results and insights are given for both full-information and bandit information settings.
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Inverse Jacobian and related topics for certain superelliptic curves
To an algebraic curve C over the complex numbers one can associate a non-negative integer g, the genus, as a measure of its complexity.
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Het miljard deeltjes probleem
Promotor: Prof.dr. S. Portegies Zwart
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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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Error bounds for discrete tomography
Promotores: K.J. Batenburg, B. Koren
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Joint Lectures on Evolutionary Algorithms
Lezing
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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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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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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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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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Isogeny graphs, modular polynomials, and applications
This thesis has three main parts. The first part gives an algorithm to compute Hilbert modular polynomials for ordinary abelian varieties with maximal real multiplication. Hilbert modular polynomials of a given level b give a way of finding all of the abelian varieties that are b-isogeneous to any given…
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Causal Discovery from High-Dimensional Data in the Large-Sample Limit
Developing robust algorithms and theory for establishing cause-effect relationships from observational data that scale up to large data sets
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Images of Galois representations
Promotores: S.J. Edixhoven, P.Parent
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Applications of quantum annealing in combinatorial optimization
Quantum annealing belongs to a family of quantum optimization algorithms designed to solve combinatorial optimization problems using programmable quantum hardware. In this thesis, various methods are developed and tested to understand how to formulate combinatorial optimization problems for quantum…