Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.

Abstract: The eigenmode theory, which uses the modal currents solved from surface differential equations (SDEs) as the basis functions of the method of moment (MoM), has been applied to the analysis ...

Distributions: Normal, Gamma, Non-Central Chi-Squared (some functions are delegated to Apache commons-math). Models: Black Scholes, Bachelier, SABR, ZABR, CEV, etc. The library is available for Java ...

Brownian motion (BM) is a stochastic model that has been extensively studied in physics, finance, and engineering. However, its potential use in cryptographic applications remains underexplored. This ...

Silent data errors are raising concerns in large data centers, where they can propagate through systems and wreak havoc on long-duration programs like AI training runs. SDEs, also called silent data ...

Silent data corruption errors in large server farms have become a major concern of cloud users, hyperscalers, processor manufacturers and the test community. Silent data errors (also called silent ...

The model equations are as follows. $$ \begin{align*} \dfrac{\mathrm dS}{\mathrm dt} &= -\frac{\beta c S I}{N}, \\ \dfrac{\mathrm dI}{\mathrm dt} &= \frac{\beta c S I ...

Abstract: We consider the problem of estimating the expectation over a convex polyhedron specified by a set of linear inequalities. This problem encompasses a multitude of financial applications ...