Change Point Detection In Continuous Integration Performance Tests

Software testing is an integral part of the development of embedded systems. Among other reasons, tests are frequently used to ensure that a system meets all the specifications, which is especially important when designing systems for the medical industry. Software changes that have a detrimental impact on a real-time system's performance can...

Exploring the Potential of Performance Bounds in Multi-Source Domain Adaptation

Currently, trained machine learning models are readily available, but their training data might not be (for example due to privacy reasons). This thesis investigates how pre-trained models can be combined for performance on all their source domains, without access to data. This problem is formulated as a Multiple-Source Domain Adaptation (MSA)...

An international study on the collection and combination of optimised algorithms or predicting progression in Alzheimer’s Disease

Early detection of Alzheimer's Disease (AD), i.e. before symptom onset, would provide the opportunity for development and testing of interventions at earlier stages, when the disease process may still be altered or interrupted. Computer algorithms combining machine learning with non-invasive imaging and other biomarkers for AD have been...

A novel surrogate-assisted evolutionary algorithm applied to partition-based ensemble learning

We propose a novel surrogate-assisted Evolutionary Algorithm for solving expensive combinatorial optimization problems. We integrate a surrogate model, which is used for fitness value estimation, into a state-of-the-art P3-like variant of the Gene-Pool Optimal Mixing Algorithm (GOMEA) and adapt the resulting algorithm for solving non-binary...

Strength in Numbers: Improving Generalization with Ensembles in Machine Learning-based Profiled Side-channel Analysis

The adoption of deep neural networks for profiled side-channel attacks provides powerful options for leakage detection and key retrieval of secure products. When training a neural network for side-channel analysis, it is expected that the trained model can implement an approximation function that can detect leaking side-channel samples and, at...

Automated Pricing Suggestions

As Machine Learning is becoming more accessible to small businesses, thanks to the rapid advance in computing power, smaller start-ups such as Sjauf (a ride sharing start-up) are starting to get interested in implementing Machine Learning solutions in their product. Sjauf needed a system that could automatically tell its customers how much a...

Tree-based ensemble methods for sensitivity analysis of environmental models: A performance comparison with Sobol and Morris techniques

Complex environmental models typically require global sensitivity analysis (GSA) to account for non-linearities and parametric interactions. However, variance-based GSA is highly computationally expensive. While different screening methods can estimate GSA results, these techniques typically impose restrictions on sampling methods and input...