512 search results for “algorithms” in the Public website
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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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A much sharper picture of the universe with new algorithms and supercomputers
With new algorithms and supercomputers, an incredibly detailed radio map of the universe was created. Now astronomers can look at radio data of galaxies with much more precision. This was published in Nature Astronomy by Leiden PhD student Frits Sweijen and colleagues.
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Hanshu Yu
Science
h.yu@liacs.leidenuniv.nl | +31 71 527 2727
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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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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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Marcello Bonsangue
Science
m.m.bonsangue@liacs.leidenuniv.nl | +31 71 527 7095
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Nurbolat Kenbayev
Science
n.kenbayev@liacs.leidenuniv.nl | +31 71 527 2727
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Arend-Jan Quist
Science
a.quist@liacs.leidenuniv.nl | +31 71 527 2727
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Francien Dechesne
Faculteit Rechtsgeleerdheid
f.dechesne@law.leidenuniv.nl | +31 71 527 7608
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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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DNA expressions - A formal notation for DNA
Promotores: J.N. Kok, H.J. Hoogeboom
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Thomas Bäck wint IEEE Award
Thomas Bäck wins the 2015 IEEE CIS Evolutionary Computation Pioneer Award for his contributions in synthesizing evolutionary computation.
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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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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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Guiding evolutionary search towards innovative solutions
Promotors: Prof.dr. T.H.W. Bäck, Prof.dr. B. Sendhoff (Technische Universität Darmstadt)
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Complex multiplication of abelian surfaces
Promotor: Peter Stevenhagen
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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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Statistical Science
The research programme Statistical Science is concerned with the analysis and interpretation of masses of data, the quantification of uncertainty using probability models, and the development and benchmarking of algorithms and methods with these aims.
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Joint Lectures on Evolutionary Algorithms
Lecture
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Quantum Lab (aQa)
Quantum computing is a novel paradigm for computation, which is nearing real-world impact with the coming generation of limited, but nonetheless powerful quantum devices.
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The gravitational billion body problem
Promotor: Prof.dr. S. Portegies Zwart
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Error bounds for discrete tomography
Promotores: K.J. Batenburg, B. Koren
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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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Joint Lectures on Evolutionary Algorithms - November 2023
Lecture
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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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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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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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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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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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SAILS Lunch Time Seminar: Rüya Koçer
Lecture
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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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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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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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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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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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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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Frank Takes
Science
f.w.takes@liacs.leidenuniv.nl | +31 71 527 7143
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Vasilii Bokov
Science
v.bokov@liacs.leidenuniv.nl | +31 71 527 2727
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Felix Frohnert
Science
f.frohnert@liacs.leidenuniv.nl | +31 71 527 2727
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Vincent Croft-
Science
v.a.croft@liacs.leidenuniv.nl | +31 71 527 4799
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Jan van Rijn
Science
j.n.van.rijn@liacs.leidenuniv.nl | +31 71 527 7492
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Resource allocation in networks via coalitional games
Promotor: F. Arbab, R. De Nicola, Co-Promotor: M. Tribastone