We analyze two popular semidefinite programming relaxations for quadratically constrained quadratic programs with matrix variables. These relaxations are based on vector lifting and on matrix lifting; ...
Vol. 21, No. 1, ET 20th Anniversary Colloquium: Automated Inference and the Future of Econometrics (Feb., 2005), pp. 158-170 (13 pages) This paper proposes a new class of heteroskedastic and ...
M.Sc. in Applied Mathematics, Technion (Israel Institute of Technology) Ph.D. in Applied Mathematics, Caltech (California Institute of Technology) [1] A. Melman (2023): “Matrices whose eigenvalues are ...
Determining an unknown signal from a set of measurements is a fundamental problem in science and engineering. However, as the number of free parameters defining the signal increases, its tomographic ...
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