In this paper we extend the micro-macro decomposition based asymptotic-preserving scheme developed in [3] for the single species Boltzmann equation to the multispecies problems. A...
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
This work considers the independent component analysis (ICA) of quaternion random vectors. In particular, we focus on the Gaussian case, and therefore the ICA problem is solved by...
Alternating optimization algorithms for canonical polyadic decomposition (with/without nonnegative constraints) often accompany update rules with low computational cost, but could...
Software architectures shift the focus of developers from lines-of-code to coarser-grained elements and their interconnection structure. Architecture description languages (ADLs) ...