Thesis Proposals
Below you will find a number of thesis topic proposals for Bachelor or Master's theses. Contact Viktor Bengs or Marcel Wever for individual thesis topics.
Link to the Institute for Informatics information page on Bachelor and Master's theses.
(Most recently added topics first.)
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Implementation of Plackett-Luce-based Methods for Dyad Ranking (Ba)
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Deep-PLNets for Dyad Ranking (Ma)
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Single-Peaked Preferences for Modeling Political Orientation (Ba/Ma)
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LSH based Similarity Search for Ranking Data using Shingling (Ba/Ma)
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Python Package for Statistical Rank Models (Ba/Ma)
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Forward Regression for Online Algorithm Selection (BA/MA)
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Can I trust my Explainable AI algorithm? Evaluating and Benchmarking xAI algorithms. (Ba/Ma)
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Efficient Optimization of Hierarchical Multi-Label Classifier Ensembles (Ba/Ma)
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Fuzzy Pattern Trees as Deep Fuzzy Systems (Ba/Ma)
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Learning from Imprecise Data with an Adjusted Infimum Loss (Ba/Ma)
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Deep Aggregation Autoencoders (Ma)
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A systematic review of listwise learning to rank (Ba)
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Mixed Dyad Ranking (Ba/Ma)
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Calibration of scoring classifiers: Survey and empirical comparison (Ba/Ma)
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Rank Aggregation for Incomplete Rankings (Ba/Ma)
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Conformal prediction for top-k-rankings (Ba/Ma)
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Solving label ranking problems via error-correcting output codes (Ba/Ma)
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Probabilistic Circuits for Preferences (Ba/Ma)
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Data-driven adaptation of weighted rank correlation measures (Ba/Ma)