Abstract: To approximate functions of a single variable by using linear interpolation is routine in empirical studies. Here, we consider approximating functions of several variables in a similar ...
Abstract: Graph sparsification underlies a large number of algorithms, ranging from approximation algorithms for cut problems to solvers for linear systems in the graph Laplacian. In its strongest ...
This repository contains the official code implementation for the paper "Query-Guided Predicate Decoupling and Prototype Approximation Learning for Scene Graph Generation" All our experiments are ...
Graph algorithms can be expressed as sequences of linear, algebra-like operations through the use of the adjacency matrix. Adjacency matrices are used to represent graphs instead of vertices and edges ...
Approximation Approximation is a replacement of some mathematical objects by others, in one sense or another, close to the original ones. When interpolating, the interpolating function strictly passes ...
Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...
The object of this paper is a theoretical study of the convergence of approximation methods (Galerkin and finite difference methods) to compute eigenelements of a closed linear operator T in a Banach ...
This paper offers a qualitative theoretical analysis of the error that may arise when a linear programming calculation is used to solve a problem involving some ...
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