Pattern mining methods for graph data have largely been restricted to ground features, such as frequent or correlated subgraphs. Kazius et al. have demonstrated the use of elaborat...
Andreas Maunz, Christoph Helma, Tobias Cramer, Ste...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Hierarchical clustering methods are widely used in various scientific domains such as molecular biology, medicine, economy, etc. Despite the maturity of the research field of hie...
Abstract. There is a variety of methods for ranking objectives in multiobjective optimization and some are difficult to define because they require information a priori (e.g. esta...
The pre-tabular statistical disclosure control (SDC) method of data swapping is the preferred method for protecting Census tabular data in some National Statistical Institutes, in...