This paper describes a fast and robust approach to recovering structure and motion from video frames. It rst describes a robust recursive factorization method for a ne projection. Using the Least Median of Squares (LMedS) criterion, the method estimates the dominant 3D a ne motion and discards feature points regarded as outliers. The computational cost of the overall procedure is reduced by com...

We discuss in this paper the numerical approximation of fluid-structure interaction (FSI) problems dealing with strong added-mass effect. We propose new semi-implicit algorithms based on inexact block-LU factorization of the linear system obtained after the space-time discretization and linearization of the FSI problem. As a result, the fluid velocity is computed separately from the coupled pre...

We discuss the origin of causal set structure and the emergence of classical space and time in the universe. Given that the universe is a closed self-referential quantum automaton with a quantum register consisting of a vast number of elementary quantum subregisters, we find two distinct but intimately related causal sets. One of these is associated with the factorization and entanglement prope...

We introduce the federated multi-view matrix factorization method that extends learning framework to with multiple data sources. Our is able learn model without transferring user's personal a central server. As far as we are aware this first provide recommendations using factorization. The rigorously evaluated on three datasets production settings. Empirical validation confirms outperforms simp...

Abstract Properties can be tailored by tuning composition in high-order spaces. For spaces with complex phase behavior, modeling the properties as a function of and distribution remains formidable challenge. We present materials structure–property factorization (MSPF) an approach to automate such data identify synergistic interactions. MSPF is interpretable machine learning algorithm that coupl...

In this paper‎, ‎an efficient dropping criterion has been used to compute the IUL factorization obtained from Backward Factored APproximate INVerse (BFAPINV) and ILU factorization obtained from Forward Factored APproximate INVerse (FFAPINV) algorithms‎. ‎We use different drop tolerance parameters to compute the preconditioners‎. ‎To study the effect of such a dropping on the quality of the ILU ...

We consider the problem of structure prediction for sparse LU factorization with partial pivoting. In this context, it is well known that the column elimination tree plays an important role for matrices satisfying an irreducibility condition, called the strong Hall property. Our primary goal in this paper is to address the structure prediction problem for matrices satisfying a weaker assumption...