Searched for: mods_note_programme_s%3A%22Computer%255C+Science%255C+%257C%255C+Data%255C+Science%255C+and%255C+Technology%22
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Ómarsdóttir, Þórunn (author)In this thesis, we study automatically generating explanatory reports for anomalous incidents in a train control system (TCS) using Natural Language Generation (NLG). A TCS is a type of safety-critical software that allows train controllers to correctly set the tracks for a train to pass. The goal of this research is to process the majority of...master thesis 2020
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Pocchiari, M. (author)Recommender Systems assist the user by suggesting items to be consumed based on the user's history. The topic of diversity in recommendation gained momentum in recent years as additional criterion besides recommendation accuracy, to improve user satisfaction. Accuracy and diversity in recommender systems coexist in a delicate trade-off due to...master thesis 2020
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Seale, Colm (author)Synthetic lethality (SL) arises between two genes when loss of function of both genes would lead cells to become inviable. This can be exploited for therapy, where a drug is used to selectively kill diseased cells by perturbing one gene of an SL pair where the other gene is inactive (e.g. through naturally occurring mutation). Computational...master thesis 2020
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Gong, B. (author)With advancements in Internet and technology, it has become increasingly easy for people to enjoy music. Users are able to access millions of songs through music streaming services like Spotify, Pandora, and Deezer. Access to such large catalogs created a need for relevant song recommendations. Music recommender systems assist users in finding...master thesis 2020
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SOILIS, Panagiotis (author)Deep learning models have achieved state-of-the-art performance on several image classification tasks over the past years. Several studies claim to approach or even surpass human-levels of performance when using such models to classify images. However, these architectures are notoriously complex, thus making their interpretation a challenge....master thesis 2020
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Simion-Constantinescu, Andrei (author)This thesis presents a novel self-supervised approach of learning visual representations from videos containing human actions. Our approach tackles the complex problem of learning without the need of labeled data by exploring to what extent the ideas successfully used for images can be transferred, adapted and extended to videos for action...master thesis 2020
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Sudharsan, S. (author)Deep learning has enabled technologies that have been perceived complex or impossible a few years ago. Deep learning models can be used to solve several complex problem statements thereby making it a prominent field of research. With the advancements of Deep learning models, their application in domains have diversified. One prominent use-case...master thesis 2020
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Kosiorek, Anna (author)Steel production is a complex problem, and little has been done to improve it with the usage of Reinforcement Learning techniques. Most studies focus on decomposing it into sub-problems, instead of tacking it as a whole. Research has shown promising results in the area of safe policy improvement on toy problems. These algorithms are not only...master thesis 2020
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Mostert, C. (author)High-level music classification tasks such as automatic music mood annotation impose several challenges, both from a psychological and a machine learning point of view. Ground truth labels for these tasks at hand are hard to define due to the abstract and aesthetic nature of the data, being largely dependent on human psychology and perception....master thesis 2020
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Albers, Nele (author)We analyze the internal representations that deep Reinforcement Learning (RL) agents form of their environments and whether these representations correspond to what such agents should ideally learn. The purpose of this comparison is both a better understanding of why certain algorithms or network architectures perform better than others and the...master thesis 2020
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Mazzola, Gabriele (author)Time-varying network data are essential in several real-world applications, such as temperature forecasting and earthquake classification. Spatial and temporal dependencies characterize these data and, therefore, conventional machine learning tools often fail to learn these joint correlations from data. On the one hand, hybrid models to learn...master thesis 2020
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Iancu, Bianca (author)Network data are essential in applications such as recommender systems, social networks, and sensor networks. A unique characteristic that these data encompass is the coupling between the data values and the underlying network structure on which these data are defined. Graph Neural Networks (GNNs) have been designed as tools to extend the...master thesis 2020
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Zabłocki, Bartosz (author)When driving a car, people can usually predict the intention of other road users with high confidence. They can spot small variations in a recent trajectory, take into account road infrastructure, traffic rules and other factors, which influence a future trajectory. As a result, they can interact with other drivers smoothly and safely. Even...master thesis 2020
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Morales Martinez, Francisco (author)Weak baselines have been present in Information Retrieval (IR) for<br/>decades. They have been associated with IR progress stagnation, baseline<br/>selection bias to publish results more readily, and models’ effectiveness<br/>reproducibility issues that hinder the validation of results by independent<br/>research teams. Weak baselines have been...master thesis 2020
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Michielsen, Lieke (author)Since the revolution of single-cell RNA-sequencing, the number of available datasets has increased enormously. In these datasets, cell identification is mainly done manually, which is subjective and time-consuming. As a consequence, most datasets are annotated at a different resolution. This is not surprising as cell types form a hierarchy, but...master thesis 2020
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Bălan, Alexandru (author)Nowadays, most users access the web through search engine portals. However, information needs can often be ill-defined or too broad to be solvable by a list of results the user has to scroll through, which implies that he is most likely required to refine the need by himself to reach the desired result. In recent years, researchers have...master thesis 2019
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Sirocki, Jeffrey (author)Objective: This thesis aided the 113 Suicide Prevention (113), the national suicide prevention center for The Netherlands, by investigating technical solutions for the helpline, implementing an e-learning prototype housing six suicidal personas within a conversational agent model, and evaluating and analyzing an experiment on its effect, which...master thesis 2019
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Krishnaraj, Manoj (author)Recommender systems (RS) often use a large amount of data for a marginal gain in performance. This thesis investigates the data minimization in Recommender Systems, which is not well studied in the literature. This thesis extends the data minimization principles advocated in GDPR and studies its effects on recommender systems. Minimizing data...master thesis 2019
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Booij, Tim (author)The amount of people and devices connected through the Internet has been growing at a rapid pace; as of June 2019 58,8% of the world’s population and billions of devices are joined by this vast network of information resources and services. Not every Internet user however has benign intentions. Cybercriminals use this technology for their own...master thesis 2019
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Li, Xin (author)Visual context plays a key role in many computer vision tasks, and performance of eye/gaze-tracking methods also benefit from it. However, the size of contextual information (e.g. full face image) is very large w.r.t the primary input i.e. cropped image of the eye. This adds large computational costs to the algorithm and makes it inefficient,...master thesis 2019
Searched for: mods_note_programme_s%3A%22Computer%255C+Science%255C+%257C%255C+Data%255C+Science%255C+and%255C+Technology%22
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