Recently, Balcan and Blum [1] suggested a theory of learning based on general similarity functions, instead of positive semi-definite kernels. We study the gap between the learnin...
The hierarchical non-negative matrix factorization (HNMF) is a multilayer generative network for decomposing strictly positive data into strictly positive activations and base vect...
Sven Rebhan, Julian Eggert, Horst-Michael Gro&szli...
— This paper presents a novel control strategy based on a non-smooth Lyapunov function to guarantee the stability of the system in the whole motion space. Three control laws that...
This paper presents the design of a selective-actuation flexure parallel mechanism that can provide three independent translational motions. The mechanism can be used as an ultra p...
The Non-negative Matrix Factorization technique (NMF) has been recently proposed for dimensionality reduction. NMF is capable to produce a region- or partbased representation of o...