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DocParser: Hierarchical Structure Parsing of Document Renderings
Johannes Rausch, Octavio Martinez, Fabian Bissig +2
Translating renderings (e. g. PDFs, scans) into hierarchical document structures is extensively demanded in the daily routines of many real-world applications. However, a holistic,…
Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences
Mathias Kraus, Stefan Feuerriegel
Predicting the remaining useful life of machinery, infrastructure, or other equipment can facilitate preemptive maintenance decisions, whereby a failure is prevented through timely…
Improving Heart Rate Variability Measurements from Consumer Smartwatches with Machine Learning
Martin Maritsch, Caterina Bérubé, Mathias Kraus +5
The reactions of the human body to physical exercise, psychophysiological stress and heart diseases are reflected in heart rate variability (HRV). Thus, continuous monitoring of HR…
Personalized Purchase Prediction of Market Baskets with Wasserstein-Based Sequence Matching
Mathias Kraus, Stefan Feuerriegel
Personalization in marketing aims at improving the shopping experience of customers by tailoring services to individuals. In order to achieve this, businesses must be able to make…
RankQA: Neural Question Answering with Answer Re-Ranking
Bernhard Kratzwald, Anna Eigenmann, Stefan Feuerriegel
The conventional paradigm in neural question answering (QA) for narrative content is limited to a two-stage process: first, relevant text passages are retrieved and, subsequently,…
Public decision support for low population density areas: An imbalance-aware hyper-ensemble for spatio-temporal crime prediction
Cristina Kadar, Rudolf Maculan, Stefan Feuerriegel
Crime events are known to reveal spatio-temporal patterns, which can be used for predictive modeling and subsequent decision support. While the focus has hitherto been placed on ar…
Sample Complexity Bounds for Recurrent Neural Networks with Application to Combinatorial Graph Problems
Nil-Jana Akpinar, Bernhard Kratzwald, Stefan Feuerriegel
Learning to predict solutions to real-valued combinatorial graph problems promises efficient approximations. As demonstrated based on the NP-hard edge clique cover number, recurren…