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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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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
document
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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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
document
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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Bhaskaran, Prajit (author)
A learning curve displays the measure of accuracy/error on test data of a machine learning algorithm trained on different amounts of training data. They can be modeled by parametric curve models that help predict accuracy improvement through curve extrapolation methods. However, these learning curves have only been mainly generated from default...
bachelor thesis 2022
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Poeth, Ole (author)
Cognitive processes have been used in recent years for context sensing and this has shown promising results. Multiple sets of features have shown good performance but no set of features has been determined the best for classifying gaze data. This paper looks at different feature sets and the heterogeneity of gaze signals from subjects and...
bachelor thesis 2022
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Barták, Patrik (author)
Causal machine learning deals with the inference of causal relationships between variables in observational datasets. <br/>For certain datasets, it is correct to assume a causal graph where information about unobserved confounders can only be obtained through noisy proxies, and CEVAE aims to address this case. <br/>The number of dimensions of...
bachelor thesis 2022
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Fledderus, Eddy (author)
The domains of the negotiation can vary significantly. It is possible that a domain is very cooperative, where both agents can receive a high utility; the opposite is also possible, where the domain is very competitive and the agents cannot both get a high utility. In the same manner, the agents can have different strategies leading to a...
bachelor thesis 2022
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Charlot, Amaury (author)
Different methods have been studied to predict earthquakes, but the results are still far from optimal. Due to their seemingly dynamic and unpredictable nature, it has been very hard to find data correlating with earthquakes happening. But recently, various research has been done using neural networks, and some has suggested that it could...
bachelor thesis 2022
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van Dijk, Max (author)
Mind wandering is a phenomenon that is used to describe moments where a person's attention appears to shift away to something that is not related to the primary task, which can have a negative influence on the task performance. In this research, the aim is to create a viable algorithm that can automatically detect mind wandering based on eye...
bachelor thesis 2022
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Burnik, Elmedin (author)
Machine learning is becoming more and more applied within business and academia alike. This has led researchers to look inwards and discuss whether the current way of teaching and learning machine learning is the right way. Within this train of thought, one must investigate the characteristics of teaching and learning. Namely, what are the...
bachelor thesis 2022
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Rosenberg, Jaron (author)
The purpose of this research is to reduce food waste by monitoring the ripening process of strawberries in order to optimize the harvesting time. To improve the moment of harvest, we need to know the ripeness of a strawberry. Using data from different color ranges and spaces we should be able to predict the ripeness of a strawberry on a 1-10...
bachelor thesis 2022
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Neut, Oliver (author)
Automatic machine learning is a subfield of machine learning that automates the common procedures faced in predictive tasks. The problem of one such procedure is automatic data augmentation, where one desires to enrich the existing data to increase model performance. In relational data repositories, the data is stored in normal form. This causes...
bachelor thesis 2022
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TSIFOUTIS KAZOLIS, Kostas (author)
Mechanical metamaterials are materials that appear to have unusual elastic mechanical properties, with the most prominent being a negative Poisson’s ratio. The key to their unique properties lies in the microarchitecture of the material rather than the material itself. For advanced applications in the realm of prosthetics, such as form matching,...
master thesis 2022
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Hennink, Birgitte (author)
master thesis 2022
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Bui, NAM THANG (author)
Although there are many promising applications of a learning curve in machine learning, such as model selection, we still know very little about what factors influence their behaviours. The aim is to study the impact of the inherent characteristics of the datasets on the learning shapes, which are noise, discretized input and dimensionality. We...
bachelor thesis 2022
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Mulder, Tijmen (author)
From 2019 into 2021, phishing incidents tripled, while phishing was found to be the largest used cyberattack vector. One commonly used type of phishing is a credential phishing attack over email. This is an act where an attacker tries to steal credential information from a target via a phishing website. This phishing website is delivered to the...
master thesis 2022
document
Potjer, Mark (author)
Master thesis about machine learning in materials science
master thesis 2022
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