Julie Nutini
Title
Cited by
Cited by
Year
Linear convergence of gradient and proximal-gradient methods under the polyak-łojasiewicz condition
H Karimi, J Nutini, M Schmidt
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2016
3362016
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
1462015
A survey of non-gradient optimization methods in structural engineering
W Hare, J Nutini, S Tesfamariam
Advances in Engineering Software 59, 19-28, 2013
1242013
A derivative-free approximate gradient sampling algorithm for finite minimax problems
W Hare, J Nutini
Computational Optimization and Applications 56 (1), 1-38, 2013
482013
Let's Make Block Coordinate Descent Go Fast: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence
J Nutini, I Laradji, M Schmidt
arXiv preprint arXiv:1712.08859, 2017
232017
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
172016
Optimizing damper connectors for adjacent buildings
K Bigdeli, W Hare, J Nutini, S Tesfamariam
Optimization and Engineering 17 (1), 47-75, 2016
152016
“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 (4), 645-655, 2019
132019
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
72019
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
72016
Greed is good: greedy optimization methods for large-scale structured problems
J Nutini
University of British Columbia, 2018
62018
Optimal design of damper connectors for adjacent buildings
K Bigdeli, W Hare, J Nutini, S Tesfamariam
Comput Struct, submitted for publication, 2013
12013
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
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Articles 1–17