We prove that multilinear (tensor) analogues of many efficiently computable problems in
numerical linear algebra are NP-hard. Our list includes: determining the feasibility of a …

The portfolio optimization model has limited impact in practice because of estimation issues
when applied to real data. To address this, we adapt two machine learning methods …

We derive bounds on couplings in the standard model effective field theory (SMEFT) as a
consequence of causality and the analytic structure of scattering amplitudes. In the SMEFT …

Evolutionary algorithms have been proven to be effective in solving multi-objective
optimization problems. However, their performance deteriorates progressively in handling …

We survey two aspects of mixed-integer nonlinear programming which have attracted less
attention (so far) than solution methods, solvers and applications: namely, whether the class …

Polyhedral relaxations have been incorporated in a variety of solvers for the global
optimization of mixed-integer nonlinear programs. Currently, these relaxations constitute the …

A bstract We derive new constraints on massive gravity from unitarity and analyticity of
scattering amplitudes. Our results apply to a general effective theory defined by Einstein …

Sum of squares (SOS) optimization has been a powerful and influential addition to the
theory of optimization in the past decade. Its reliance on relatively large-scale semidefinite …

We perform a new analysis of electron-proton scattering data to determine the proton electric
and magnetic radii, enforcing model-independent constraints from form factor analyticity. A …

We completely characterize sections of the cones of nonnegative polynomials, convex
polynomials and sums of squares with polynomials supported on circuits, a genuine class of …