Showing news articles whose tags include: Optimization
Julian Hall, in collaboration with his former PhD student Qi Huangfu, has been awarded the prize for the best paper of 2015 in Computational Optimization and Applications. The article describes the novel numerical linear algebra techniques required by their efficient parallel implementation of the dual revised simplex method.
Congratulation to Jacek Gondzio who has been awarded a three year EPSRC grant entitled "Computational Design Optimization of Large-Scale Building Structures: Methods, Benchmarking & Applications".
Applications are invited for a 2-year postdoctoral position in the area of optimization with a particular focus on practical methods used in financial mathematics.
The CoCoA [NIPS 2014] / CoCoA+ [ICML 2015] distributed optimization algorithm developed in a duo of papers with two co-authors from Edinburgh (Martin TakÃ¡Ä, Peter Richtarik) has won the MLconf Industry Impact Student Research Award. The award goes to our coauthor Virginia Smith (UC Berkeley).
Applications are invited for a Postdoctoral Research Associate in optimization in the School of Mathematics at the University of Edinburgh, United Kingdom. The post is available from 1st September 2016 for a 3 year fixed ...
Two former members of the School, Olivier Fercoq and John Pearson each won a 2nd prize at the 17th IMA Fox Prize in Numerical Analysis:
Congratulations to Dominik Csiba for winning the Best Contribution Award (2nd place) at “Optimization and Big Data 2015” for his paper “Stochastic dual coordinate ascent with adaptive probabilities” ...
John Pearson, a Whittaker Fellow in the School of Mathematics, and Olivier Fercoq, a former Postdoc in the School, are among the six shortlisted finalists for the 17th Leslie Fox prize.
The School of Mathematics will join with computer scientists at Edinburgh University, as well as partners at 4 other major UK universities (Cambridge, Oxford, UCL and Warwick) in realising the vision of the Alan Turing Institute as the UK's hub for new research in data science.