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Approximations for Hierarchical and Lower-Bounded Clustering and the Complexity of Minimum-Error Triangulation
(2024-03-28)
Clustering deals with the problem of finding structures in data. Given a number k we search for a good partition of a set of data points into at most k sets, where the sets of the partition are called clusters. In the ...
Uncertainty Reduction in Diffusion Magnetic Resonance Imaging Tractography
(2024-04-04)
Diffusion Magnetic Resonance Imaging (dMRI) is currently the only non-invasive method capable of mapping the geometry and microstructure of major white matter tracts in vivo. This technique measures the movement of water ...
Towards enabling precision medicine in Alzheimer's disease and Parkinson's disease
(2024-03-21)
Alzheimer's disease and Parkinson's disease are prominent progressive neurodegenerative diseases, with a significant clinical and economic impact on patients, their families, and society as a whole. Despite numerous clinical ...
On the Usability of Coverage-Based Fuzzing of C/C++ Programs
(2024-02-15)
Even though the foundations for fuzzing were laid more than 30 years ago, it did not play a role in industry or academia for a long time. Interestingly, the popularity of fuzzing has risen for top-tier companies and academia ...
Deep Dynamic Language Models
(2024-03-15)
This thesis investigates the domain of deep dynamic language models, focusing on the integration of temporal dynamics to enhance language modeling and its application in various tasks, such as text generation, recommendation ...
Generative Adversarial Networks for Semantic Image Synthesis and Unconditional Synthesis with Limited Data
(2024-02-15)
Generative modeling of images is an important task aimed at synthesizing new images that are indistinguishable from real samples. The ability to generate diverse, realistic- looking images holds numerous applications, ...
Multiple Objective Learning for Effective Knowledge Graph Embedding
(2023-03-15)
Over the past decade, knowledge graphs (KGs) have become popular for capturing structured domain knowledge. Knowledge graphs particularly allow the effortless integration of heterogeneous data into a coherent model. Besides ...