In this study Principal Component Analysis (PCA), Non-negative Matrix Factorization (NMF) and Nonnegative Tensor Factorization (NTF) are applied as dimension reduction methods in ...
Alexey Andriyashin, Jussi Parkkinen, Timo Jaaskela...
In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...
Transactional memory systems promise to reduce the burden of exposing thread-level parallelism in programs by relieving programmers from analyzing complex inter-thread dependences...
In the present paper, we investigate the approximation of a function by a polynomial with floating-point coefficients; we are looking for the best approximation in the L2 sense....
Modern vehicles possess an increasing number of software and hardware components that are integrated in electronic control units (ECUs). Finding an optimal allocation for all comp...