About:
Solving convex optimisation problems is the principal requirement in computational optimisation. Ever-increasing problem size, particularly as a result of the growing importance and scale of data analysis, is driving the development of novel techniques for solving convex optimisation problems using high performance computing systems. Further information about the workshop can be found here.
Speakers:
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Stephen Boyd, Stanford University - Operator Splitting for Conic Optimisation via Homogeneous Self-Dual Embedding
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Jacek Gondzio, University of Edinburgh - Inexact Search Directions and Matrix-Free Second-Order Methods for Optimisation
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Julian Hall, University of Edinburgh - Parallelising the Dual Revised Simplex Method
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Raphael Hauser, University of Oxford - The Role of Convex Optimisation in Optimal Alignments of Random Sequences
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Daniel Kuhn, Ecole Polytechnique Federale de Lausanne - Generalised Gauss Inequalities via Semidefinite Programming
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Daniel Ralph, University of Cambridge - Capacity Decisions in Electricity Production Under Risk Aversion and Risk Trading