Abstract: We solve the convergence case of the generalized Baker–Schmidt problem for simultaneous approximation on affine subspaces, under natural diophantine type conditions. In one of our theorems, ...

Abstract: In this paper, we propose a variational approach for the affine point set matching problems under the Bayesian probabilistic framework. A directed acyclic graph is provided for the ...

We propose a smooth approximation l(0)-norm constrained affine projection algorithm (SL0-APA) to improve the convergence speed and the steady-state error of affine ...

We establish a central limit theorem and a large deviations principle for affine point processes, which are stochastic models of correlated event timing widely used in finance and economics. These ...

A comprehensive C++ implementation of the theoretical framework presented in "Efficient Subspace Approximation Algorithms" by Shyamalkumar and Varadarajan, featuring advanced algorithmic optimizations ...

In recent years, the application of function approximators, such as neural networks and polynomials, has ushered in a new stage of development in solving optimal control problems. However, considering ...