Robert Mansel Gower
Robert Mansel Gower
Assistant professor in Machine Learning, at Telecom-Paristech
確認したメール アドレス: telecom-paristech.fr - ホームページ
タイトル引用先
Randomized iterative methods for linear systems
RM Gower, P Richtárik
SIAM Journal on Matrix Analysis and Applications 36 (4), 1660-1690, 2015
782015
Stochastic block BFGS: Squeezing more curvature out of data
R Gower, D Goldfarb, P Richtárik
International Conference on Machine Learning, 1869-1878, 2016
622016
Stochastic dual ascent for solving linear systems
RM Gower, P Richtárik
arXiv preprint arXiv:1512.06890, 2015
372015
Randomized quasi-Newton updates are linearly convergent matrix inversion algorithms
RM Gower, P Richtárik
SIAM Journal on Matrix Analysis and Applications 38 (4), 1380-1409, 2017
252017
A new framework for the computation of Hessians
RM Gower, MP Mello
Optimization Methods and Software 27 (2), 251-273, 2012
162012
Tracking the gradients using the Hessian: A new look at variance reducing stochastic methods
RM Gower, NL Roux, F Bach
arXiv preprint arXiv:1710.07462, 2017
92017
Stochastic quasi-gradient methods: Variance reduction via Jacobian sketching
RM Gower, P Richtárik, F Bach
arXiv preprint arXiv:1805.02632, 2018
82018
Accelerated stochastic matrix inversion: general theory and speeding up BFGS rules for faster second-order optimization
R Gower, F Hanzely, P Richtárik, SU Stich
Advances in Neural Information Processing Systems, 1619-1629, 2018
82018
Action constrained quasi-Newton methods
RM Gower, J Gondzio
arXiv preprint arXiv:1412.8045, 2014
82014
Higher-order Reverse Automatic Differentiation with emphasis on the third-order.
R Gower, AL Gower
72013
Linearly convergent randomized iterative methods for computing the pseudoinverse
RM Gower, P Richtárik
arXiv preprint arXiv:1612.06255, 2016
62016
Sketch and project: randomized iterative methods for linear systems and inverting matrices
RM Gower
arXiv preprint arXiv:1612.06013, 2016
62016
Hessian matrices via automatic differentiation
RM Gower, MP Mello
Universidade Estadual de Campinas, Instituto de Matemática, Estatística e …, 2010
62010
Computing the sparsity pattern of Hessians using automatic differentiation
RM Gower, MP Mello
ACM Transactions on Mathematical Software (TOMS) 40 (2), 10, 2014
52014
Characterising particulate random media from near-surface backscattering: A machine learning approach to predict particle size and concentration
AL Gower, RM Gower, J Deakin, WJ Parnell, ID Abrahams
EPL (Europhysics Letters) 122 (5), 54001, 2018
22018
Greedy stochastic algorithms for entropy-regularized optimal transport problems
BK Abid, RM Gower
arXiv preprint arXiv:1803.01347, 2018
22018
Improving SAGA via a probabilistic interpolation with gradient descent
A Bibi, A Sailanbayev, B Ghanem, RM Gower, P Richtárik
arXiv preprint arXiv:1806.05633, 2018
12018
Conjugate Gradients: The short and painful explanation with oblique projections
RM Gower
tech. report, University of Edinburgh, Maxwell Institute for Mathematical …, 2014
12014
Optimal mini-batch and step sizes for SAGA
N Gazagnadou, RM Gower, J Salmon
arXiv preprint arXiv:1902.00071, 2019
2019
SGD: General Analysis and Improved Rates
RM Gower, N Loizou, X Qian, A Sailanbayev, E Shulgin, P Richtarik
arXiv preprint arXiv:1901.09401, 2019
2019
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