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Fundamental Barriers in Optimisation, Statistics, and Signal Processing

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If you have a question about this talk, please contact Dr Hansen .

When solving optimisation problems such as linear programming (LP), semidefinite programming (SDP), basis pursuit (BP), LASSO , or training neural networks, we often discuss algorithms in terms of their ability to achieve an adequately small suboptimality of the objective function. In this talk we ask a different question: Do optimisation algorithms find good approximations to exact optima? We will see that the answer to this question is surprisingly nuanced, with implications for the theory of numerical condition and complexity theory.

This talk is part of the Applied and Computational Analysis series.

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Hybrid: JDB Seminar Room, Engineering Department or Zoom: https://cam-ac-uk.zoom.us/j/88498768580?pwd=1zjqKCU8AiRcd7ZR6SXBTjc0ScElsc.1 Heffers Bookshop events 2009 KLUG Lecture Theatre, MRC-LMB, Francis Crick Avenue, Cambridge Biomedical Campus, CB2 0QH

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