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X-ORIGINAL-URL:https://optimisation.doc.ic.ac.uk
X-WR-CALDESC:Events for Computational Optimisation Group
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DTSTART:20180101T000000
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BEGIN:VEVENT
DTSTART;TZID=UTC:20190206T160000
DTEND;TZID=UTC:20190206T170000
DTSTAMP:20260429T012815
CREATED:20190123T095139Z
LAST-MODIFIED:20190123T095139Z
UID:1208-1549468800-1549472400@optimisation.doc.ic.ac.uk
SUMMARY:Seminar: Model-based design of optimal experiments using exact confidence regions
DESCRIPTION:Title: Model-based design of optimal experiments using exact confidence regions\nSpeaker: Dr Radoslav Paulen\nAffiliation: Institute of Information Engineering\, Automation and Mathematics\, Slovak University of Technology\nLocation: 218 Huxley Building\nTime: 16:00 – 17:00 \nAbstract. This talk discusses a model-based optimal experiment design (OED) for nonlinear systems. OED represents a methodology for optimizing the geometry of the parametric joint-confidence regions\, which are obtained in an a posteriori analysis of the parameter estimates. The optimal design is achieved by using the available (experimental) degrees of freedom such that more informative measurements are obtained. Unlike the commonly used approaches\, which base the OED procedure upon the linearized CRs\, we explore a path where we explicitly consider the exact CRs in the OED framework. We use a methodology for a finite parameterization of the exact CRs within the OED problem. The employed techniques give the OED problem as a finite-dimensional mathematical program of a bilevel nature. We discuss the use of several solution techniques tailored to the problem. Finally\, we illustrate the methodology on few small-scale case studies and compare the resulting optimal designs with the commonly used linearization-based approach. \nBiography. Dr Radoslav Paulen currently works at the Institute of Information Engineering\, Automation and Mathematics at Slovak University of Technology in Bratislava. He does research in Modelling\, Parameter Estimation\, Optimization and Advanced Control of Dynamic Systems. The group of Dr Paulen concentrates on research in estimation and optimal control of nonlinear dynamic systems with applications in chemical and biochemical processes. The main research topics include (i) guaranteed and statistical parameter estimation\, and (ii) dynamic optimization\, global optimization\, predictive control.
URL:https://optimisation.doc.ic.ac.uk/event/seminar-model-based-design-of-optimal-experiments-using-exact-confidence-regions/
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BEGIN:VEVENT
DTSTART;TZID=UTC:20190226T140000
DTEND;TZID=UTC:20190226T150000
DTSTAMP:20260429T012815
CREATED:20190214T121614Z
LAST-MODIFIED:20190214T143922Z
UID:1212-1551189600-1551193200@optimisation.doc.ic.ac.uk
SUMMARY:Seminar: Generalized maximum entropy estimation
DESCRIPTION:Title: Generalized maximum entropy estimation\nSpeaker: Dr David Sutter\nAffiliation: Institute for Theoretical Physics\, ETH Zurich\nLocation: 217 Huxley Building\nTime: 14:00 – 15:00 \nAbstract. We consider the problem of estimating a probability distribution that maximizes the entropy while satisfying a finite number of moment constraints\, possibly corrupted by noise. Based on duality of convex programming\, we present a novel approximation scheme using a smoothed fast gradient method that is equipped with explicit bounds on the approximation error. \nThis is joint work with T. Sutter\, P. Esfahani\, and J. Lygeros (arXiv:1708.07311). \nBiography. Dr David Sutter is a postdoctoral researcher at ETH Zurich\, working on mathematical aspects of quantum information theory. He obtained his PhD degree from the Institute for Theoretical Physics at ETH Zurich under the supervision of Prof. Renato Renner. Dr Sutter’s interests lie in the intersection of quantum mechanics\, information theory\, and mathematical physics. To understand the fundamental limits of information processing and communications\, he utilizes tools from matrix analysis\, optimization theory and probability theory.
URL:https://optimisation.doc.ic.ac.uk/event/seminar-generalized-maximum-entropy-estimation/
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