Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
In many scientific applications, significant time is spent tuning codes for a particular highperformance architecture. Tuning approaches range from the relatively nonintrusive (...
Albert Hartono, Boyana Norris, Ponnuswamy Sadayapp...
We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....
Privacy-preserving data mining (PPDM) is an emergent research area that addresses the incorporation of privacy preserving concerns to data mining techniques. In this paper we prop...
For the analysis of learning processes and the underlying changes of the shape of excitatory synapses (spines), 3-D volume samples of selected dendritic segments are scanned by a ...
Andreas Herzog, Bernd Michaelis, Gerald Krell, Kat...