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eess.SY2021★ 4 cited
A Convex Optimization Approach to Learning Koopman Operators
Mario Sznaier
Koopman operators provide tractable means of learning linear approximations of non-linear dynamics. Many approaches have been proposed to find these operators, typically based upon…
eess.SY2020★ 1 cited
Peak Estimation and Recovery with Occupation Measures
Jared Miller, Didier Henrion, Mario Sznaier
Peak Estimation aims to find the maximum value of a state function achieved by a dynamical system. This problem is non-convex when considering standard Barrier and Density methods…
eess.SY2012★ 2 cited
Probabilistic Optimal Estimation and Filtering under Uncertainty
Fabrizio Dabbene, Mario Sznaier, Roberto Tempo
The classical approach to system identification is based on stochastic assumptions about the measurement error, and provides estimates that have random nature. Worst-case identific…