Linear approximation is a method used to estimate the value of a function near a given point using the tangent line at that point. This technique simplifies complex functions into a linear form ...

However, in existing works, the log-linear models are all derived based on first-order linearization approximation, which seemingly goes against their successful applications in INS initial alignment ...

Sets of multivariable functions are described for which worst case errors in linear approximation are larger than those in approximation by neural networks. A theoretical framework for such a ...

An error term is a residual variable produced by statistical or mathematical modeling.

William F. Sharpe, A Linear Programming Approximation for the General Portfolio Analysis Problem, The Journal of Financial and Quantitative Analysis, Vol. 6, No. 5 (Dec., 1971), pp. 1263-1275 ...

When constructing the confidence regions of the regression parameters, one had to either directly estimate the asymptotic covariance matrix involving the estimation of the unknown density function of ...

Formulate linear and integer programming problems for solving commonly encountered optimization problems. Understand how approximation algorithms compute solutions that are guaranteed to be within ...