Lascoux polynomials have been recently introduced to prove polynomiality of the maximum-likelihood degree of linear concentration models. We find the leading coefficient of the Lascoux polynomials (type C) and their generalizations to the case of general matrices (type A) and skew symmetric matrices (type D). In particular, we determine the degrees of such polynomials. As an application, we find the degree of the polynomial $\delta(m,n,n-s)$ of the algebraic degree of semidefinite programming, and when $s=1$ we find its leading coefficient for types C, A and D.
翻译:为了证明线性浓度模型最大相似度的多元性,最近引入了Lascuux聚度模型。我们发现了Lascuux聚度模型(C类)的主要系数及其对一般矩阵(A类)和Skew对称矩阵(D类)的概括性系数。特别是,我们决定了这种多元度。作为一个应用,我们发现了半definite编程的代谢度多度值(m,n,n-s)的数值,当我们发现C类、A类和D类主要系数为1美元时。