Artificial intelligence has recently experienced remarkable advances, fueled by large
models, vast datasets, accelerated hardware, and, last but not least, the transformative …

The supplementary materials contain more background on convex functions, wavelets and
empirical processes, as well as tools to prove lower bounds, alternative assumptions based …

The Lambert W is a transcendental function defined by solutions of the equation W exp (W)=
x. For real values of the argument, x, the W-function has two branches, W0 (the principal …

In recent years, significant progress has been made in explaining the apparent hardness of
improving upon the naive solutions for many fundamental polynomially solvable problems …

This paper focuses on computing the convex conjugate operation that arises when solving
Euclidean Wasserstein-2 optimal transport problems. This conjugation, which is also …

We present a method to efficiently solve the optimal transportation problem for a general
class of strictly convex costs. Given two probability measures supported on a discrete grid …

We construct a family of beryllium (Be) multiphase equation of state (EOS) models that
consists of a baseline (“optimal”) EOS and variations on the baseline to account for physics …

Modeling distributions on Riemannian manifolds is a crucial component in understanding
non-Euclidean data that arises, eg, in physics and geology. The budding approaches in this …

Computational convex analysis algorithms have been rediscovered several times in the past
by researchers from different fields. To further communications between practitioners, we …

Information bottleneck (IB) and privacy funnel (PF) are two closely related optimization
problems which have found applications in machine learning, design of privacy algorithms …