A common method to solve expensive function evaluation problem is using Bayesian Global Optimization, instead of Evolutionary Algorithms.

A modern ship design process is subject to a wide variety of constraints such as safety constraints, regulations, and physical constraints.

This thesis seeks to combine two different research topics; Multi-Objective Optimization and Complex Network Analysis.

Promotores: Prof.dr. T.H.W. Bäck, Prof.dr. M.R.V. Chaudron, Co-Promotor: M.T.M. Emmerich

Promotores: Prof.dr. T.H.W. Bäck, Prof.dr. M. Bongards (Cologne University)

Optimization tasks in practice have multifaceted challenges as they are often black box, subject to multiple equality and inequality constraints and expensive to evaluate.

This thesis involves three topics: benchmarking discrete optimization algorithms, empirical analyses of evolutionary computation, and automatic algorithm configuration.

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.

This thesis covers several aspects of quantum algorithms for near-term quantum computers and its applications to quantum chemistry and material science.

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…

Industrial manufacturing processes, such as the production of steel or the stamping of car body parts, are complex semi-batch processes with many process steps, machine parameters and quality indicators.

Continuous optimization is never easy: the exact solution is always a luxury demand and the theory of it is not always analytical and elegant.

Promotor: Prof.dr. H.A.G. Wijshoff

Multi-objective evolutionary computation aims to find high quality (Pareto optimal) solutions that represent the trade-off between multiple objectives.

Congres/symposium

Promotor: Prof.dr.ir. E. Deprettere

In design optimization problems, engineers typically handcraft design representations based on personal expertise, which leaves a fingerprint of the user experience in the optimization data. Thus, learning this notion of experience as transferrable design features has potential to improve the performance…

This thesis focuses on addressing four research problems in designing embedded streaming systems.

Promotor: Prof.dr. A. P. IJzerman, Co-Promotor: L.H. Heitman

Machine Learning is becoming a more and more substantial technology for industry.

Over several decades, a variety of computational methods for drug discovery have been proposed and applied in practice. With the accumulation of data and the development of machine learning methods, computational drug design methods have gradually shifted to a new paradigm, i.e. deep learning methods…

De Duitse hoogleraar Information Systems and Statistics Heike Trautmann aanvaardde deze maand de Pascalleerstoel bij LIACS, het informatica-instituut aan de Universiteit Leiden. Trautmanns belangrijkste vakgebieden zijn evolutionary multiobjective optimisation en data science, waar ook LIACS sterk in…

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.

In this work we describe three methods to improve the performance of Quantum Field Theory calculations.

The next generation of high-contrast imaging instruments on space-based observatories requires sophisticated wavefront sensing and control in addition to a high-performance coronagraph.

Promotie

Promotor: G.P. van Wezel, Co-Promotor: E. Vijgenboom

Promotors: Prof.dr. T.H.W. Bäck, Prof.dr. B. Sendhoff (Technische Universität Darmstadt)

On a structural level, the properties featured by a majority of mechanical metamaterials can be ascribed to the finite number of soft internal degrees-of freedom allowing for low-energy deformations.

Congres/symposium

Onderzoekers van het Leiden Institute of Advanced Computer Science (LIACS) ontwikkelen een systeem dat automatisch waarschuwingen uitstuurt wanneer onderdelen van motoren de eerste verschijnselen van vermoeidheid beginnen te vertonen. Het project duurt 4 jaar.

Lezing, Seminar

Wiskunde en Natuurwetenschappen

Promotie

Promotie

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…

Promotie

Promotie

Promotie

In deep reinforcement learning, searching and learning techniques are two important components. They can be used independently and in combination to deal with different problems in AI, and have achieved impressive results in game playing and robotics. These results have inspired research into artificial…

Promotores: C.A.M.J.J. van den Hondel, V. Meyer, Co-promotor: A.F.J. Ram

In this thesis, the discovery and optimization is described of chemical tools to study the N-acylethanolamine (NAE) biosynthetic pathway.

In this thesis it is posed that the central object of preference discovery is a co-creative process in which the Other can be represented by a machine. It explores efficient methods to enhance introverted intuition using extraverted intuition's communication lines.

Promotores: T.H.W. Bäck, Y. Tan, Co-promotor: M.T.M. Emmerich