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Understanding the Role of Explanation Modality in AI-assisted decision-making

Robbemond, Vincent (author)

Advances in artificial intelligence and machine learning have led to a steep rise in the adoption of AI to augment or support human decision-making across domains.<br/>There has been an increasing body of work addressing the benefits of model interpretability and explanations to help end-users or other stakeholders decipher the inner workings of...

master thesis 2023

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Behind the Botnet: Evaluating Avalanche's security controls using a reconstruction of its anatomy from forensic evidence

Miedema, Fieke (author)

How did Avalanche, a botnet with an active lifetime of 8 years while serving 20+ malware families, ensure a smooth operation of business? Avalanche had the attention of security researchers and law enforcement, yet it managed to persevere for a long period of time.<br/>In this work, we answer this question by analyzing Avalanche’s security...

master thesis 2022

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Understanding weight-magnitude hyperparameters in training binary networks

Quist, Joris (author)

Binary Neural Networks (BNNs) are compact and efficient by using binary weights instead of real-valued weights. Current BNNs use latent real-valued weights during training, where several training hyper-parameters are inherited from real-valued networks. The interpretation of several of these hyperparameters is based on the magnitude of the real...

master thesis 2022

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Investigating fair rankers under the expected exposure framework

Visser, Maaike (author)

As the amount of information available in the world grows, Information Retrieval (IR) systems have become an integral part of day to day life. They determine what subset of the large pool of information is shown to people. IR algorithms determine which items should be returned in response to a query and rank the results in a ranked list.<br/...

master thesis 2022

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Deep Statistical Solver for Distribution System State Estimation

Habib, Benjamin (author)

Whereas in the past, Distribution Systems played a passive role in connecting customers to electricity, Distribution System Operators (DSOs) will have to take in the future a more active role in monitoring and regulating the network to deal with the new behaviors and dynamics of the system brought by the energy transition. State Estimation, a...

master thesis 2022

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Predicting Delays in Software Deliveries using Networked Classification at ING

Moelchand, Pravesh (author)

Delays in the delivery of software projects and the corresponding cost and schedule overruns have been common problems in the software industry for years. A challenge within software project management is to make accurate effort estimations during planning. Software projects are complex networks, with multiple dependencies between software tasks...

master thesis 2022

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Bi-VAKs: Bi-Temporal Versioning Approach for Knowledge Graphs

Meijer, Lisa (author)

Over time Linked Data collections are continuously subject to change because of numerous reasons. Users could insert new observations, or they could rectify erroneous statements in these knowledge graphs. In order not to lose historically import information, this trend of evolving Linked Data collections increases the need to version these...

master thesis 2022

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Benchmarking of viral quasispecies assembly algorithms

Narkhede, Rucha (author)

Viral quasispecies refers to viral populations that comprises of numerous viral strains closely related to each other due to within-host evolution or co-infection. The reconstruction of viral strain-specific genomes using sequencing reads is referred to as viral quasispecies assembly, and it is also crucial to determine the relative abundances...

master thesis 2022

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Obtaining Smoothly Navigable Approximation Sets in Bi-Objective Multi-Modal Optimization with an Application to Prostate HDR Brachytherapy Automated Treatment Planning

Scholman, Renzo (author)

Even if a Multi-modal Multi-Objective Evolutionary Algorithm (MMOEA) is designed to find all locally optimal approximation sets of a Multi-modal Multi-objective Optimization Problem (MMOP), there is a risk that the found approximation sets are not smoothly navigable because the solutions belong to various niches, which reduces the insight for...

master thesis 2022

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Determining epitope specificity of T-cell receptors with Transformers

Khan, Abdul Rehman (author)

Transformers have dominated the field of natural language processing due to their competency in learning complex relationships within a sequence. Reusing a pre-trained transformer for a downstream task is known as Trans-fer learning. Transfer learning restricts the transformer to a fixed vocabulary; modification in transformer implementation...

master thesis 2022

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Node Survivability and Dynamics of the Dutch Municipality Network

Manolopoulos, Ioannis (author)

This thesis’ research concerns the time-dynamics of a complex geographical network of municipalities, i.e. the Dutch Municipality Network over the period 1830-2019. By analysing 190 years of socioeconomic statistical data and applying contemporary tooling from network science and geographic information systems (GIS), the findings from this...

master thesis 2022

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Characterization and Mitigation of High-Confidence Errors Through the Use of Human-In-The-Loop Methods: Domain Expert Driven Approach to Model Development

Hoogland, Pavel (author)

In the use of Machine Learning systems, attaining the trust of those that are the end-users can often be difficult. Many of the current state-of-the-art systems operate as Black-Boxes. Errors produced by these Black-Box systems, without further explanation as to why these decisions were made, will deteriorate trust. This effect is especially...

master thesis 2022

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REAL Reinforcement Learning: Planning with adversarial models

Foffano, Daniele (author)

Model-Based Reinforcement Learning (MBRL) algorithms solve sequential decision-making problems, usually formalised as Markov Decision Processes, using a model of the environment dynamics to compute the optimal policy. When dealing with complex environments, the environment dynamics are frequently approximated with function approximators (such as...

master thesis 2022

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The State of Data Streaming Practices at ING

Kanya Paramita Koesoemo, Kanya (author)

The development of data stream processing has become one of the key themes in the database and distributed system community throughout the world as data has grown on a large scale and in a range of industries over the last several years. Because data stream processing is a relatively new breakthrough in data-driven approaches, several teams at...

master thesis 2021

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Know what it does not know: Improving Offline Deep Reinforcement Learning with Uncertainty Estimation

Smit, Jordi (author)

Offline reinforcement learning, or learning from a fixed data set, is an attractive alternative to online reinforcement learning. Offline reinforcement learning promises to address the cost and safety implications of taking numerous random or bad actions online, which is a crucial aspect of traditional reinforcement learning that makes it...

master thesis 2021

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Exact Machine Learning: Improving Space and Speed of MaxSAT Solvers for Correlation Clustering

Marchal, Maxim (author)

Clustering is an important unsupervised learning task, with many applications in machine learning, computer vision, formal program verification and finance. Heuristic approaches such as local search are an excellent strategy for estimating the optimal solution, but they run the danger of getting stuck in local optima. Furthermore, it is non...

master thesis 2021

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Unsupervised Manifold Alignment with TopoGAN: Aligning multi-modal biological data without correspondence information available across modalities

Singh, Akash (author)

Single-cell multi-modal omics promises to open new doors in bioinformatics by measuring different aspects of cells, thus offering multiple perspectives on the underlying biological phenomenon. Although simultaneous multi-modal measurement protocols do exist, their inherent technical limitations necessitate focus on single modality measurements....

master thesis 2021

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Experience Sharing Conversational Agent for Type II Diabetes

Saravanan, Nash (author)

In this work, a conversational interaction was designed and implemented to test the effect of references to past events or shared experiences rephrased into motivational phrases within the context of working towards a diet related goal that can assist with type II diabetes over multiple sessions.<br/>Prior works that utilized a memory typically...

master thesis 2021

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Frequency learning for structured CNN filters with Gaussian fractional derivatives

Saldanha, Nikhil (author)

A structured CNN filter basis allows incorporating priors about natural image statistics and thus require less training examples to learn, saving valuable annotation time. Here, we build on the Gaussian derivative CNN filter basis that learn both the orientation and scale of the filters. However, this Gaussian filter basis definition depends on...

master thesis 2021

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Understanding Context Effects in the Evaluation of Music Similarity

van den Berg, Michiel (author)

This work analyses context effect in the evaluation of music similarity performed by human annotators to better understand the impact of context effects in the current annotation protocol of Music Information Retrieval Evaluation eXchange (MIREX). Human annotators are known to be subjective when giving similarity judgements. The Audio Music...

master thesis 2021