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Feirstein (student), D.S. (author), Koryakovskiy, I. (author), Kober, J. (author), Vallery, H. (author)Reinforcement learning is a powerful tool to derive controllers for systems where no models are available. Particularly policy search algorithms are suitable for complex systems, to keep learning time manageable and account for continuous state and action spaces. However, these algorithms demand more insight into the system to choose a...conference paper 2016
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Panichella, A. (author), Alexandru, Carol V. (author), Panichella, Sebastiano (author), Bacchelli, A. (author), Gall, Harald C. (author)Research has yielded approaches to predict future defects in software artifacts based on historical information, thus assisting companies in effectively allocating limited development resources and developers in reviewing each others' code changes. Developers are unlikely to devote the same effort to inspect each software artifact predicted...conference paper 2016
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Knijnenburg, Theo A. (author), Klau, Gunnar W (author), Lorio, Francesco (author), Garnett, Mathew J. (author), McDermott, Ultan (author), Shmulevich, I (author), Wessels, L.F.A. (author)Mining large datasets using machine learning approaches often leads to models that are hard to interpret and not amenable to the generation of hypotheses that can be experimentally tested. We present ‘Logic Optimization for Binary Input to Continuous Output’ (LOBICO), a computational approach that infers small and easily interpretable logic...journal article 2016
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Psyllidis, A. (author)The study of dynamic spatial and social phenomena in cities has evolved rapidly in the recent years, yielding new insights into urban dynamics. This evolution is strongly related to the emergence of new sources of data for cities (e.g. sensors, mobile phones, online social media etc.), which have potential to capture dimensions of social and...doctoral thesis 2016
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Ghavamian, F. (author), Tiso, P. (author), Simone, A. (author)We demonstrate a Model Order Reduction technique for a system of nonlinear equations arising from the Finite Element Method (FEM) discretization of the three-dimensional quasistatic equilibrium equation equipped with a Perzyna viscoplasticity constitutive model. The procedure employs the Proper Orthogonal Decomposition-Galerkin (POD-G) in...journal article 2017
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Liu Cheng, Alexander (author), Bier, H.H. (author), Mostafavi, Sina (author)This paper presents a new instance in a series of discrete proof-of-concept implementations of comprehensively intelligent built-environments based on Design-to-Robotic-Production and -Operation (D2RP&O) principles developed at Delft University of Technology (TUD). With respect to D2RP, the featured implementation presents a customized...conference paper 2017
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Degeler, V. (author), Heydenrijk-Ottens, L.J.C. (author), Luo, D. (author), van Oort, N. (author)We perform analysis of public transport data from March 2015 from The<br/>Hague, the Netherlands, combined from three sources: static network information, automatic vehicles location (AVL) and automated fare collection (AFC) data. We highlight the effect of bunching swings, and show that this phenomenon can be extracted using unsupervised...conference paper 2018
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Liem, C.C.S. (author), Langer, Markus (author), Demetriou, A.M. (author), Hiemstra, Annemarie M.F. (author), Achmadnoer Sukma Wicaksana, Sukma (author), Born, Marise Ph. (author), König, Cornelis J. (author)In a rapidly digitizing world, machine learning algorithms are increasingly employed in scenarios that directly impact humans. This also is seen in job candidate screening. Data-driven candidate assessment is gaining interest, due to high scalability and more systematic assessment mechanisms. However, it will only be truly accepted and trusted...book chapter 2018
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Suryanarayana, Gowri (author), Lago, Jesus (author), Geysen, Davy (author), Aleksiejuk, Piotr (author), Johansson, Christian (author)Recent research has seen several forecasting methods being applied for heat load forecasting of district heating networks. This paper presents two methods that gain significant improvements compared to the previous works. First, an automated way of handling non-linear dependencies in linear models is presented. In this context, the paper...journal article 2018
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The I in Team: Mining Personal Social Interaction Routine with Topic Models from Long-Term Team DataZhang, Y. (author), Olenick, Jeffrey (author), Chang, Chu-Hsiang (author), Kozlowski, Steve W.J. (author), Hung, H.S. (author)Social interaction plays a key role in assessing teamwork and collaboration. It becomes particularly critical in team performance when coupled with isolated, confined, and extreme conditions such as undersea missions. This work investigates how social interactions of individual members in a small team evolve during the course of a long...conference paper 2018
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Zhu, Jichen (author), Liapis, Antonios (author), Risi, Sebastian (author), Bidarra, Rafael (author), Michael Youngblood, G. (author)Growing interest in eXplainable Artificial Intelligence (XAI) aims to make AI and machine learning more understandable to human users. However, most existing work focuses on new algorithms, and not on usability, practical interpretability and efficacy on real users. In this vision paper, we propose a new research area of eXplainable AI for...conference paper 2018
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Neerincx, M.A. (author), Koldijk, Saskia (author), Kraaij, Wessel (author)Employees often report the experience of stress at work. In the SWELL project we investigate how new context aware pervasive systems can support knowledge workers to diminish stress. The focus of this paper is on developing automatic classifiers to infer working conditions and stress related mental states from a multimodal set of sensor data ...journal article 2018
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Virgolin, M. (author), Alderliesten, Tanja (author), Bel, Arjan (author), Witteveen, C. (author), Bosman, P.A.N. (author)The recently introduced Gene-pool Optimal Mixing Evolutionary Algorithm for Genetic Programming (GP-GOMEA) has been shown to find much smaller solutions of equally high quality compared to other state-of-the-art GP approaches. This is an interesting aspect as small solutions better enable human interpretation. In this paper, an adaptation of...conference paper 2018
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Automatic classification of fine-grained soils using CPT measurements and Artificial Neural NetworksReale, C. (author), Gavin, Kenneth (author), Librić, Lovorka (author), Jurić-Kaćunić, Danijela (author)Soil classification is a means of grouping soils into categories according to a shared set of properties or characteristics that will exhibit similar engineering behaviour under loading. Correctly classifying site conditions is an important, costly, and time-consuming process which needs to be carried out at every building site prior to the...journal article 2018
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Ruiz Arenas, S. (author)Typically, emerging system failures have a strong impact on the performance of industrial systems as well as on the efficiency of their operational and servicing processes. Being aware of these, maintenance and repair researchers have developed multiple failure detection and diagnosis techniques that allow early recognition of system or...doctoral thesis 2018
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Kouw, W.M. (author)Artificial intelligence, and in particular machine learning, is concerned with teaching computer systems to perform tasks. Tasks such as autonomous driving, recognizing tumors in medical images, or detecting suspicious packages in airports. Such systems learn by observing examples, i.e. data, and forming a mathematical description of what types...doctoral thesis 2018
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Liu, S. (author), Oosterlee, C.W. (author), Bohte, Sander M. (author)This paper proposes a data-driven approach, by means of an Artificial Neural Network (ANN), to value financial options and to calculate implied volatilities with the aim of accelerating the corresponding numerical methods. With ANNs being universal function approximators, this method trains an optimized ANN on a data set generated by a...journal article 2019
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Paltrinieri, Nicola (author), Comfort, Louise (author), Reniers, G.L.L.M.E. (author)Risk assessment has a primary role in safety-critical industries. However, it faces a series of overall challenges, partially related to technology advancements and increasing needs. There is currently a call for continuous risk assessment, improvement in learning past lessons and definition of techniques to process relevant data, which are...journal article 2019
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Dwivedi, Yogesh K. (author), Hughes, Laurie (author), Ismagilova, Elvira (author), Aarts, Gert (author), Coombs, Crispin (author), Crick, Tom (author), Duan, Yanqing (author), Dwivedi, Rohita (author), Janssen, M.F.W.H.A. (author)As far back as the industrial revolution, significant development in technical innovation has succeeded in transforming numerous manual tasks and processes that had been in existence for decades where humans had reached the limits of physical capacity. Artificial Intelligence (AI) offers this same transformative potential for the augmentation...journal article 2019
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Kim, Jaehun (author), Picek, S. (author), Heuser, Annelie (author), Bhasin, Shivam (author), Hanjalic, A. (author)Profiled side-channel analysis based on deep learning, and more precisely Convolutional Neural Networks, is a paradigm showing significant potential. The results, although scarce for now, suggest that such techniques are even able to break cryptographic implementations protected with countermeasures. In this paper, we start by proposing a new...journal article 2019