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Table of Contents
Pattern Mining
clustering
privacy and fairness
(social) network analysis and computational social science
dimensionality reduction and autoencoders
domain adaptation
sketching, sampling, and binary projections
graphical models and causality
(spatio- ) temporal data and recurrent neural networks
collaborative filtering and matrix completion.
clustering
privacy and fairness
(social) network analysis and computational social science
dimensionality reduction and autoencoders
domain adaptation
sketching, sampling, and binary projections
graphical models and causality
(spatio- ) temporal data and recurrent neural networks
collaborative filtering and matrix completion.