Searched for: contributor%3A%22Verwer%2C+S.E.+%28graduation+committee%29%22
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Cosma, Bianca (author)
<b>Motivation: </b>The development of automated protein function prediction models is essential in closing the gap between the large amount of protein sequence data available and the fraction of validly annotated data. Recent approaches to function prediction rely on unsupervised deep learning models, through which protein sequences are...
bachelor thesis 2022
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Hendrikx, Roemer (author)
In the past 8 years, Bitcoin has dominated the cryptocurrency markets and drawn attention from academia, developers and legislators alike. Bitcoin has been praised for its impact on decentralizing trust and currencies but also criticized for its volatility and energy-inefficient consensus mechanism. To improve its limitations, in 2016, payment...
master thesis 2022
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Mrahorović, Mirza (author)
Deep Neural Network (DNNs) have increased significantly in size over the past decade. Partly due to this, the accuracy of DNNs in image classification and speech recognition tasks has increased as well. This enables a great potential for such models to be applied in real-world applications. However, due to their size, the compute and power...
master thesis 2021
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van der Laan, Niek (author)
Finding defects in proposed changes is one of the biggest motivations and expected outcomes of code review, but does not result as often as expected in actually finding defects. Just-in-time (JIT) defect prediction focuses on predicting bug-introducing changes, which can help with efficient allocation of inspection time according to the defect...
master thesis 2021
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d' Estalenx, Antoine (author)
IoT devices keep entering our homes with the promise of delivering more services and enhancing user experience; however, these new devices also carry along an alarming number of vulnerabilities and security issues. In most cases, the users of these devices are completely unaware of the security risks that connecting these devices entail. Current...
master thesis 2021
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de Heer, Hugo (author)
MalPaCA makes use of unsupervised machine learning to provide malware capability assessment by clustering the temporal behaviour of malware network packet traces. A comparative analysis was performed on various clustering algorithms to determine the best clustering algorithm in terms of network behaviour discovery. The clustering algorithms...
bachelor thesis 2021
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te Wierik, Ruben (author)
Real-time sequence clustering is the problem of clustering an infinite stream of sequences in real time with limited memory. A variant of the k-medoids algorithm called <i>SeqClu </i>is the suggested approach, representing a cluster with <i>p </i>most representative sequences of the cluster, called prototypes, to solve the problem of maintaining...
bachelor thesis 2021
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van der Knaap, Leon (author)
One of the planning problems encountered by the Dutch Railways (NS) at shunting yards is the train unit shunting problem (TUSP). This problem considers idle train units that have to be parked, be cleaned, undergo regular maintenance, and be reconfigured into the scheduled departing train compositions. A local search algorithm is being developed...
master thesis 2021
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Jia, Zhoufan (author)
Suppose we have a target radiance distribution, a light source, and a plane for receiving light. How do we design a reflector that can give a similar result as the target radiance distribution? The inverse reflector problem is of high interest for light designers and related industries, such as lamp manufacture, headlight and street light design...
master thesis 2021
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Wieffering, Tristan (author)
We propose a novel, dynamic analysis-based detection solution for formjackers. The operating principle of these formjackers, or card skimmers on the web, is typically simple, yet effective: when making a payment on webshop that has been infected with a formjacker, the submitted payment information is not just transmitted to the webshop, but also...
master thesis 2021
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van Rijn, Vincent (author)
Virtualization is the fundamental technology that enabled the widespread adoption of cloud computing. With the ever-increasing pervasiveness of the cloud computing paradigm, strong isolation guarantees and low performance overhead from isolation platforms are paramount. An ideal isolation platform offers both: an infallible isolation boundary...
master thesis 2021
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Bisesser, Dinesh (author)
An increasing digital world, comes with many benefits but unfortunately also many drawbacks. The increase of the digital world means an increase in data and software. Developing more software unfortunately also means a higher probability of vulnerabilities, which can be exploited by adversaries. Adversaries taking advantage of users and software...
master thesis 2020
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Choi, Yapkan (author)
Person re-identification based on appearance is challenging due to varying views and lighting conditions in different cameras, or when multiple persons wear similar clothing styles and color. Considering these challenges, gait patterns provide an alternative to appearance, as gait can be captured from a distance and at a low resolution. In this...
master thesis 2020
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Li, Mengze (author)
Active learning has the potential to reduce labeling costs in terms of time and money. In practical use, active learning works as an efficient data labeling strategy. Another point of view to look at active learning is to consider active learning as a learning problem, where the training data is queried by the active learner. Under this...
master thesis 2020
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Puppels, Thomas (author)
Predict-and-Optimize (PnO) is a relatively new machine learning paradigm that has attracted recent interest: it concerns the prediction of parameters that determine the value of solutions to an optimization problem, such that the optimizer ends up picking a good solution. Training estimators with standard loss functions like mean squared error...
master thesis 2020
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van Driel, R.A. (author)
Solving propositional satisfiability (SAT) and constraint programming (CP) instances has been a fundamental part of a wide range of modern applications. For this reason a lot of research went into improving the efficiency of modern SAT and CP solvers. Recently much of this research has gone into exploring the possibilities of integrating machine...
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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Liu, Xin (author)
This work proposes a method for matching images from different domains in an unsupervised manner, and detecting outlier samples in the target domain at the same time. This matching problem is made difficult by i) the different domain images that are related but under different conditions (e.g. photos of the same location captured in different...
master thesis 2018
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