On the Relationship between $\mathrm{\Lambda }$-poisedness in Derivative-Free Optimization and Outliers in Local Outlier Factor

Derivative-free optimization (DFO) is a method that does not require the calculation of gradients or higher-order derivatives of the objective function, making it suitable for cases where the objective function is non-differentiable or the computation of derivatives is expensive. This communication discusses the importance of $\mathrm{\Lambda }$-poisedness in DFO and the outliers detected by the Local Outlier Factor (LOF) on the optimization process. We discuss the relationship between $\mathrm{\Lambda }$-poisedness in derivative-free optimization and outliers in local outlier factor.