Linear convergence of gradient and proximal-gradient methods under the polyak-łojasiewicz condition H Karimi, J Nutini, M Schmidt Machine Learning and Knowledge Discovery in Databases: European Conference …, 2016 | 1064 | 2016 |

Coordinate descent converges faster with the gauss-southwell rule than random selection J Nutini, M Schmidt, I Laradji, M Friedlander, H Koepke International Conference on Machine Learning, 1632-1641, 2015 | 246 | 2015 |

A survey of non-gradient optimization methods in structural engineering W Hare, J Nutini, S Tesfamariam Advances in Engineering Software 59, 19-28, 2013 | 210 | 2013 |

Let’s Make Block Coordinate Descent Go Fast! J Nutini, I Laradji, M Schmidt, W Hare arXiv, 2017 | 69 | 2017 |

Convergence rates for greedy Kaczmarz algorithms, and faster randomized Kaczmarz rules using the orthogonality graph J Nutini, B Sepehry, I Laradji, M Schmidt, H Koepke, A Virani arXiv preprint arXiv:1612.07838, 2016 | 60 | 2016 |

A derivative-free approximate gradient sampling algorithm for finite minimax problems W Hare, J Nutini Computational Optimization and Applications 56, 1-38, 2013 | 59 | 2013 |

“Active-set complexity” of proximal gradient: How long does it take to find the sparsity pattern? J Nutini, M Schmidt, W Hare Optimization Letters 13, 645-655, 2019 | 41 | 2019 |

Are we there yet? manifold identification of gradient-related proximal methods Y Sun, H Jeong, J Nutini, M Schmidt The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 34 | 2019 |

Optimizing damper connectors for adjacent buildings K Bigdeli, W Hare, J Nutini, S Tesfamariam Optimization and Engineering 17, 47-75, 2016 | 24 | 2016 |

Greed is good: greedy optimization methods for large-scale structured problems J Nutini University of British Columbia, 2018 | 16 | 2018 |

Convergence rates for greedy Kaczmarz algorithms J Nutini, B Sepehry, A Virani, I Laradji, M Schmidt, H Koepke Conference on Uncertainty in Artificial Intelligence, 2016 | 16 | 2016 |

Let's Make Block Coordinate Descent Converge Faster: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence J Nutini, I Laradji, M Schmidt arXiv preprint arXiv:1712.08859, 2017 | 3 | 2017 |

Optimal design of damper connectors for adjacent buildings K Bigdeli, W Hare, J Nutini, S Tesfamariam Comput Struct, submitted for publication, 2013 | 2 | 2013 |

Putting the curvature back into sparse solvers J Nutini | | 2013 |

A derivative-free approximate gradient sampling algorithm for finite minimax problems JA Nutini University of British Columbia, 2012 | | 2012 |

“Active-set complexity” of proximal gradient J Nutini, M Schmidt, W Hare | | |

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

A Comparison of Random Forests and Dropout Nets for Sign Language Recognition with the Kinect N Jaques, J Nutini | | |