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Psathas, Steffano (author)A machine learning classifier can be tricked us- ing adversarial attacks, attacks that alter images slightly to make the target model misclassify the image. To create adversarial attacks on black-box classifiers, a substitute model can be created us- ing model stealing. The research question this re- port address is the topic of using model...bachelor thesis 2022
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Gogora, Kristián (author)Nonconvexity in learning curves is almost always undesirable. A machine learning model with a non-convex learning curve either requires a larger quantity of data to observe progress in its accuracy or experiences an exponential decrease of accuracy at low sample sizes, with no improvement in accuracy even when more data points are added. This...bachelor thesis 2023
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Holtgrefe, Tim (author)Microtubules are long cylindrical polymers, assembled from tubulin proteins. Microtubule ends can be visualized using fluorescence and confocal microscopy. This allows for the study of microtubule dynamics. However, the manual annotation of microtubules is laborious, which is why automated tracking methods are used. In this project we have...bachelor thesis 2023
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Wigmans, Bram (author)This paper examines whether complex high-dimensional data that describes the dynamics of a cantilever beam can be transformed into a less complex system. In particular, the transformation that is examined is the reduction of the dimension. An essential aspect of this study involves the implementation of a linear autoencoder, which is a type of...bachelor thesis 2023
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Buşe, Florena (author)Thus far the democratization of machine learning, which resulted in the field of AutoML, has focused on the automation of model selection and hyperparameter optimization. Nevertheless, the need for high-quality databases to increase performance has sparked interest in correlation-based feature selection, a simple and fast, yet effective approach...bachelor thesis 2023
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Kirchner, Joris (author)Neural network is an active research field which involves many different (unsolved) issues, for example, different types of configuration of the network architectures, training strategies, etc. Amongst these active issues, the choice of loss (or cost) functions plays an important role in how a neural network model is to be optimized (trained)...bachelor thesis 2022
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Biedma Nuñez, Pablo (author)The increasing dangers of unfairness in machine learning (ML) are becoming a frequent subject of discussion, both, in academia and popular media. Recent literature focused on introducing and assessing algorithmic solutions to bias in ML. However, there is a disconnect between these solutions and practitioners' needs. By interviewing 30 ML...bachelor thesis 2022
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Rietveld, Jip (author), de Vries, Rolf (author), de Boer, Jaap (author), Hondelink, Dieuwer (author)Amsterdam Airport Schiphol has 5 runways, each of which can be used for take-off or landing of aeroplanes. The weather heavily influences which runway configuration air traffic control might pick. Airport Forecasting Service (AFOS) predicts which configuration of runways works most efficiently given a set of expected weather conditions and the...bachelor thesis 2019
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Gaghi, Radu (author)This paper introduces a strategy for learning opponent parameters in automated negotiation and using them for future negotiation sessions. The goal is to maximize the agent’s utility while being consistent in its performance over various negotiation scenarios. While a number of reinforcement learning approaches in the field have used Q-learning,...bachelor thesis 2022
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Vigilanza Lorenzo, Pietro (author)Machine Learning (ML) models are vulnerable to adversarial samples — human imperceptible changes to regular input to elicit wrong output on a given model. Plenty of adversarial attacks assume an attacker has access to the underlying model or access to the data used to train the model. Instead, in this paper we focus on the effects the data...bachelor thesis 2022
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Dijkstra, Finn (author)Packages to encode Machine Learned models into optimization problems is an underdeveloped area, despite the advantages is could provide. The main draw of implementing Machine Learned models into optimization models, is that it allows the optimizer to better account for the human experience.<br/>Maragno D., Wiberg H. et al. constructed an...bachelor thesis 2022
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Jongejans, Liselotte (author)This research paper aims to investigate the adequacy of concepts taught during an introductory machine learning course in preparing students for subsequent courses and their professional careers. The study adopts a comprehensive approach, including a literature review, interviews with teaching staff of follow-up courses, and a survey...bachelor thesis 2023
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Trinh, Eames (author)Federated learning enables training machine learning models on decentralized data sources without centrally aggregating sensitive information. Continual learning, on the other hand, focuses on learning and adapting to new tasks over time while avoiding the catastrophic forgetting of knowledge from previously encountered tasks. Federated...bachelor thesis 2023
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van Lith, Jochem (author)Learning algorithms can perform poorly in unseen environments when they learn<br/>spurious correlations. This is known as the out-of-domain (OOD) generalization problem. Invariant Risk Minimization (IRM) is a method that attempts to solve this problem by learning invariant relationships. Motivating examples as well as counterexamples have been...bachelor thesis 2022
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Pandey, Harshitaa (author)Machine learning is still one of the most rapidly growing fields, and is used in a variety of different sectors such as education, healthcare, financial modeling etc(Jordan and Mitchell 2015). However, along with this demand for machine learning algorithms, there comes a need for ensuring that these algorithms are fair and contain little to no...bachelor thesis 2022
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Gökçe, Tolga (author)An algal bloom is defined as a rapid increase in common algae (phytoplankton) abundance in water bodies and it can occur when a group of certain environmental factors is combined. If the algae populations grow out of control, such algal blooms become problematic and cause damage to the ecosystem, such phenomena are called harmful algal blooms....bachelor thesis 2023
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Dorrestijn, Eljo (author)In the field of ecology, camera traps are important tools to collect information on the wildlife of certain areas. The problem that arises with many camera traps is that they can collect more images than a human can realistically go trough all by themselves. To help classify these images computer vision is proposed as an alternative to manual...bachelor thesis 2021
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Sihlovec, Oliver (author)Scientific problems are often concerned with optimization of control variables of complex systems, for instance hyperparameters of machine learning models. A popular solution for such intractable environments is Bayesian optimization. However, many implementations disregard dynamic evaluation costs associated with the optimization procedure....bachelor thesis 2023
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Persianov, Petr (author)Celiac disease is a genetic autoimmune disorder caused by a negative reaction to gluten associated with alterations in the gut microbiome. This study explored the potential of machine learning models and feature selection methods in identifying biomarkers for celiac disease using gut microbiome data. The performance of several machine learning...bachelor thesis 2023
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Geerts, Nathan (author)In this report, a transformer based deep learning proton dose calculation algorithm called Dose Transformer Algorithm (DoTA) is described. This model learns to predict proton dose distributions by being trained with Monte Carlo generated data. Monte Carlo is the golden standard of proton dose calculation because it is very accurate, but it has...bachelor thesis 2022