Evolving a robot's sensor morphology along with its control program has the potential to significantly improve its effectiveness in completing the assigned task, plus accommod...
Optimization problems with a nuclear norm regularization, such as e.g. low norm matrix factorizations, have seen many applications recently. We propose a new approximation algorit...
Markov decision processes (MDPs) are widely used for modeling decision-making problems in robotics, automated control, and economics. Traditional MDPs assume that the decision mak...
Handling missing data is a critical step to ensuring good results in data mining. Like most data mining algorithms, existing privacy-preserving data mining algorithms assume data ...
This paper demonstrates how machine learning methods can be applied to deal with a realworld decipherment problem where very little background knowledge is available. The goal is ...