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Subject to: Donald Goldfarb

21 de setembro de 2026 · 2 h 6 min

Notas do episódio

Donald Goldfarb is the Avanessians Professor in the IEOR Department at Columbia University. He is internationally recognized for the development and analysis of efficient and practical algorithms for solving various classes of optimization problems, including the BFGS quasi-Newton method for unconstrained optimization, steepest-edge simplex algorithms for linear programming, and the Goldfarb-Idnani algorithm for convex quadratic programming. Don has also developed highly cited methods for image de-noising, compressed sensing, matrix rank minimization, and robust portfolio selection. In addition, he has developed simplex and combinatorial algorithms for network flow problems, interior-point methods for linear, quadratic and conic programming, and alternating linearization methods for sums of convex functions. He is a Member of the National Academy of Engineering, a recipient of the INFORMS John Von Neumann Theory Prize for Fundamental, Sustained Contributions to Theory in Operations Research and the Management Sciences, the Khachiyan Prize for Life-time Accomplishments in Optimization, and 1995 Prize for Research Excellence in the Interface between Operations Research and Computer Science. He is a SIAM Fellow, and was cited in 2014 by Thomson Reuters as one of World’s Most Influential Scientific Minds (specifically, among the top 1% most cited researchers in Mathematics between 2002 and 2012). Don has served as an editor-in-chief of Mathematical Programming, an editor of the SIAM Journal on Numerical Analysis and the SIAM Journal on Optimization, an associate editor of Mathematics of Computation, Operations Research and Mathematical Programming Computation, and is an editorial board member of Foundation and Trends in Optimization.

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