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Thesis Proposals

(Most recently added topics first.)

  • Combined ranking and regression with random forests (Ba/Ma) [PDF]
  • Deep Aggregation Autoencoders (Ma) [PDF]
  • Developing of a match-three game agent (Ba/Ma) [PDF]
  • Self-training based on superset learning (Ba/Ma) [PDF]
  • Learning to aggregate the assessment of arguments in computational argumentation (Ba/Ma) [PDF]
  • A systematic review of listwise learning to rank (Ba) [PDF]
  • Implementation of the Sugeno classifier (Ba) [PDF]
  • A random generator for valued binary relations with generalized transitivity properties (Ba/Ma) [PDF]
  • Conformal prediction for top-k-rankings (Ba/Ma) [PDF]
  • Mixed Dyad Ranking (Ba/Ma) [ PDF ]
  • Non-stationary dueling bandits (Ba/Ma) [ PDF ]
  • An empirical comparison of active learning methods based on uncertainty sampling (Ba/Ma) [ PDF ]
  • Dynamic Fraud Detection Model (Ba/Ma) [ PDF ]
  • Advanced Customer Collection Scorecard (Ba/Ma) [ PDF ]
  • Calibration of scoring classifiers: Survey and empirical comparison (Ba/Ma) [ PDF ]
  • Einsatz von Bayesschen Neuronalen Netzen zur Prädiktion von dynamischen Systemen (Ba/Ma) [ PDF ]
  • Sampling nested dichotomies for multi-class classification (Ba/Ma) [PDF]
  • Multi-label classification with partial abstention (Ba/Ma) [PDF]
  • Multi-class probability estimation using nested dichotomies (Ba/Ma) [ PDF ]
  • Solving the Container Pre-Marshalling Problem using Machine Learning (Ba/Ma) [ PDF ]
  • Support Vector Classification on Noisy Data using Fuzzy Superset Losses (Ba/Ma) [ PDF ]
  • A Learning-to-Aggregate Approach to Assignment-based Similarity Induction (Ba/Ma) [ PDF ]
  • Feature selection for ranking (Ba/Ma) [ PDF ]
  • Rank Aggregation for Incomplete Rankings (Ba/Ma) [ PDF ]
  • Solving label ranking problems via error-correcting output codes (Ba/Ma) [ PDF ]
  • A critical analysis of the Kappa-measure in machine learning (Ba/Ma) [ PDF ]
  • Data-driven adaptation of weighted rank correlation measures (Ba/Ma) [ PDF ]
  • Machine learning based on analogical proportions (Ba/Ma) [ PDF ]
  • Decentralized on-line machine learning for swarm intelligence systems (Ma) [ PDF ]
  • Survival analysis on dynamic event streams (Ba/Ma) [ PDF ]
  • An analysis of chaining for multi-target prediction (Ma) [ PDF ]
  • An empirical analysis of methods for learning from data streams using recovery analysis (Ba/Ma) [ PDF ]
  • Local linear regression through data imprecisiation (Ma) [ PDF ]
  • Learning fuzzy rules from data streams (Ba/Ma) [ PDF ]
  • Predictive modeling of non-functional software properties (Ba/Ma) [ PDF ]

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