Nuit Blanche: Random Feature Roundup

In particular, we consider the mixture of two approaches: Parametric modeling based on rigid body dynamics equations and nonparametric modeling based on incremental kernel methods, with no prior information on the mechanical properties of the system. We validate the proposed technique learning the dynamics of one arm of the iCub humanoid robot. Persistence weighted Gaussian kernel for topological data analysis by Genki Kusano, Kenji Fukumizu, Yasuaki Hiraoka Topological data analysis is an emerging mathematical concept for characterizing shapes in multi-scale data. In this field, persistence diagrams are widely used as a descriptor of the input data, and can distinguish robust and noisy topological properties. Nowadays, it is highly desired to develop a statistical framework on persistence diagrams to deal with practical data.