798 search results for “algorithms” in the Public website
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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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Natural Computing
Research in the natural computing cluster covers theoretical foundations, the development of new algorithms, and interdisciplinary applications of natural computing methods.
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Error bounds for discrete tomography
Promotores: K.J. Batenburg, B. Koren
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Theory
Many important topics in computer science, such as the correctness of software, the efficiency of algorithms and the modeling of complicated systems, depend on sound theoretical underpinnings. In the Theory group, we study these fundamental building blocks and develop verification methods to prove system…
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Joint Lectures on Evolutionary Algorithms (JoLEA)
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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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Joint Lectures on Evolutionary Algorithms (JoLEA)
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Joint Lectures on Evolutionary Algorithms - June 2024
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Joint Lectures on Evolutionary Algorithms - November 2023
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Joint Lectures on Evolutionary Algorithms (JoLEA)
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Joint Lectures on Evolutionary Algorithms (JoLEA)
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Natural computing
Research in the natural computing group covers theoretical foundations, the development of new algorithms, and interdisciplinary applications of natural computing methods.
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Multicriteria Optimization and Decision Analysis
The focus of the Multicriteria Optimization and Decision Analysis (MODA) group is to develop foundations of methods in multi-objective optimization.
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Joint Lectures on Evolutionary Algorithms (JoLEA)
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Joint Lectures on Evolutionary Algorithms - April 2024
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Joint Lectures on Evolutionary Algorithms (JoLEA)
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Joint Lectures on Evolutionary Algorithms - October 2024
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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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Joint Lectures on Evolutionary Algorithms (JoLEA)
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Machine Learning
Computers are capable of making incredibly accurate predictions on the basis of machine learning. In other words, these computers can learn without intervention once they have been pre-programmed by humans. At LIACS, we explore and push the borders of what a revolutionary new generation of algorithms…
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Experience Day Data Science & Artificial Intelligence
Study information
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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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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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Joint Lectures on Evolutionary Algorithms - January 2024
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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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Sparsity-Based Algorithms for Inverse Problems
PhD defence
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Artificial Intelligence & Machine Learning
Computers are capable of making incredibly accurate predictions on the basis of machine learning. In other words, these computers can learn without intervention once they have been pre-programmed by humans. At LIACS, we explore and push the borders of what a revolutionary new generation of algorithms…
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Joint Lectures on Evolutionary Algorithms (JoLEA)
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Vasilii BokovScience
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Felix FrohnertScience
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Vincent Croft-Science
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Guilherme PerinScience
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Jan van RijnScience
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Friso SeltenFaculty Governance and Global Affairs
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Frank TakesScience
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Images of Galois representations
Promotores: S.J. Edixhoven, P.Parent
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Research
Developing computational algorithms for structural biology -A high resolution, three dimensional view of a molecule provides detailed information that help elucidate its function: by knowing the exact arrangement of atoms in a molecule, we can understand disease, develop drugs to combat them and improve…
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Computer programming
We see computer programming as an essential skill. It enables you to be self-sufficient in building tools, processing data, visualizing research output, communicating research results, etc. Moreover, it empowers you to make beautiful things.
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Artificial Intelligence (MSc)
The master’s specialisation Artificial Intelligence offers future-oriented topics in computer science with a focus on machine learning, optimization algorithms, and decision support techniques.
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Theory
Many important topics in computer science, such as the correctness of software, the efficiency of algorithms and the modeling of complicated systems, depend on sound theoretical underpinnings. In the Theory group, we study these fundamental building blocks and develop verification methods to prove system…
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Joint Lectures on Evolutionary Algorithms (JoLEA)
Lecture
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Resource allocation in networks via coalitional games
Promotor: F. Arbab, R. De Nicola, Co-Promotor: M. Tribastone
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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…
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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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Matthijs van LeeuwenScience
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Dirk van der HoevenScience
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Evert van NieuwenburgScience
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Following in nature's footsteps
A neural network mimics how our brain works. Evolutionary algorithms use the principle of natural selection to solve complex problems. This kind of 'natural computing' is being used to improve the diagnosis of Parkinson's disease or the production of steel.
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New paradigm for visual recognition
Leiden University computer scientists Yu Liu, Yanming Guo and Michael Lew are a step closer to their ultimate goal: search engines with visual recognition. Their publication of a new algorithm for fusing multi-scale deep learning representations has been received with great enthusiasm. No other algorithm…
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Mark Leiser part of winning consortium of €1.5 million Volkswagen Foundation research grant
Dr Mark Leiser, Assistant Professor in Law and Digital Technologies at eLaw, is part of a successful €1.5 million bid for a research grant from the acclaimed Volkswagen Institute on “Reclaiming individual autonomy and democratic discourse online: How to rebalance human and algorithmic decision makin…