Abstract: Training machine learning models often involves solving high-dimensional stochastic optimization problems, where stochastic gradient-based algorithms are hindered by slow convergence.

FOSDEM 2026 Michal Pleban knows his old kit inside out, and his talk on the CIDCO MailStation was one of the most interesting of FOSDEM for us – as well as the funniest. Pleban's talk, "Hacking the ...

Department of Mathematics and Computer Science, Faculty of Technology and Computer Science, University Iba Der Thiam of Thiès, Thiès, Senegal. 1) Establishment of sufficient conditions for existence ...

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 ...

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 ...

Abstract: Long-term evolution (LTE) and wireless local area network (WLAN) are often presented as opposing technologies. Hence, efficient partitioning of the spectrum resources carries critical ...

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 ...

Sampling from a given probability distribution is fundamental across various disciplines, including physics, signal processing, and artificial intelligence. In recent years, the ascendancy of flow, ...