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Fair Group-Shared Representations with Normalizing Flows
Mattia Cerrato, Marius Köppel, Alexander Segner +1
The issue of fairness in machine learning stems from the fact that historical data often displays biases against specific groups of people which have been underprivileged in the re…
Fast Private Parameter Learning and Inference for Sum-Product Networks
Ernst Althaus, Mohammad Sadeq Dousti, Stefan Kramer +1
A sum-product network (SPN) is a graphical model that allows several types of inferences to be drawn efficiently. There are two types of learning for SPNs: Learning the architectur…
Online Multi-Label Classification: A Label Compression Method
Zahra Ahmadi, Stefan Kramer
Many modern applications deal with multi-label data, such as functional categorizations of genes, image labeling and text categorization. Classification of such data with a large n…
Ensembles of Randomized Time Series Shapelets Provide Improved Accuracy while Reducing Computational Costs
Atif Raza, Stefan Kramer
Shapelets are discriminative time series subsequences that allow generation of interpretable classification models, which provide faster and generally better classification than th…