## Julie NutiniPhD, Computer Science University of British Columbia 201 2366 Main Mall Vancouver, BC, V6T 1Z4 Canada jnutini@cs.ubc.ca |

Curriculum Vitae

J. Nutini, I. Laradji, M. Schmidt and W. Hare. Let's Make Block Coordinate Descent Go Fast: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence, *submitted for publication*, 2017 [pdf][slides][poster][code].

J. Nutini, M. Schmidt and W. Hare. "Active-set complexity" of proximal gradient: How long does it take to find the sparsity pattern?,*Optimization Letters*, 2018 [pdf] [poster].

I. Laradji, J. Nutini and M. Schmidt. Graphical Newton for Huge-Block Coordinate Descent on Sparse Graphs,*NIPS Optimization Workshop*, 2017 [pdf] [poster].

H. Karimi, J. Nutini and M. Schmidt. Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Lojasiewicz Condition,*ECML-PKDD*, 2016 [pdf] [slides] [poster].

J. Nutini, B. Sepehry, I. H. Laradji, M. Schmidt, H. Koepke and A. Virani. Convergence Rates for Greedy Kaczmarz Algorithms, and Faster Randomized Kaczmarz Rules Using the Orthogonality Graph,*UAI*, 2016 [pdf] [poster] [code].

^{*}K. Bigdeli, W. Hare, J. Nutini and S. Tesfamariam. Optimizing Damper Connectors for Adjacent Buildings, *Optimization and Engineering*, 17(1):47-75, 2016 [pdf].

J. Nutini, M. Schmidt, I. H. Laradji, M. Friedlander and H. Koepke. Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection,*ICML*, 2015 [pdf] [slides] [poster] [video talk].

^{*}W. Hare, J. Nutini and S. Tesfamariam. A survey of non-gradient optimization methods in structural engineering, * Advances in Engineering Software*, 59:19-28, 2013 [pdf].

^{*}W. Hare and J. Nutini. A derivative-free approximate gradient sampling algorithm for finite minimax problems, *Computational Optimization and Applications*, 56(1):1-38, 2013 [pdf] [slides].

J. Nutini, M. Schmidt and W. Hare. "Active-set complexity" of proximal gradient: How long does it take to find the sparsity pattern?,

I. Laradji, J. Nutini and M. Schmidt. Graphical Newton for Huge-Block Coordinate Descent on Sparse Graphs,

H. Karimi, J. Nutini and M. Schmidt. Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Lojasiewicz Condition,

J. Nutini, B. Sepehry, I. H. Laradji, M. Schmidt, H. Koepke and A. Virani. Convergence Rates for Greedy Kaczmarz Algorithms, and Faster Randomized Kaczmarz Rules Using the Orthogonality Graph,

J. Nutini, M. Schmidt, I. H. Laradji, M. Friedlander and H. Koepke. Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection,

^{*} authors listed in alphabetical order