39 citations · 183 across the 49 of their papers we have counts for
6 papers · 1 filter
Positive Polynomials and Projections of Spectrahedra
João Gouveia, Tim Netzer
This work is concerned with different aspects of spectrahedra and their projections, sets that are important in semidefinite optimization. We prove results on the limitations of so…
A Note on the Convex Hull of Finitely Many Projections of Spectrahedra
Tim Netzer, Rainer Sinn
A spectrahedron is a set defined by a linear matrix inequality. A projection of a spectrahedron is often called a semidefinitely representable set. We show that the convex hull of…
On semidefinite representations of non-closed sets
Tim Netzer
Spectrahedra are sets defined by linear matrix inequalities. Projections of spectrahedra are called semidefinitely representable sets. Both kinds of sets are of practical use in po…
Closures of quadratic modules
Jaka Cimpric, Murray Marshall, Tim Netzer
We consider the problem of determining the closure of a quadratic module M in a commutative R-algebra with respect to the finest locally convex topology. This is of interest in dec…
Representation and Approximation of Positivity Preservers
Tim Netzer
We consider a closed set S in R^n and a linear operator Φon the polynomial algebra R[X_1,...,X_n] that preserves nonnegative polynomials, in the following sense: if f\geq 0 on S, t…
Exposed faces of semidefinitely representable sets
Tim Netzer, Daniel Plaumann, Markus Schweighofer
A linear matrix inequality (LMI) is a condition stating that a symmetric matrix whose entries are affine linear combinations of variables is positive semidefinite. Motivated by the…