Dmitry Kovalev, R. M. G. , Peter Richtárik, Alexander Rogozin.
Fast Linear Convergence of Randomized BFGS, 2020.
Preprint
R. M. G. , Denali Molitor, Jacob Moorman, Deanna Needell.
Adaptive Sketch-and-Project Methods for Solving Linear Systems, 2019.
Preprint
O. Sebbouh, N. Gazagnadou, S. Jelassi, F. Bach, R. M. G.
Towards closing the gap between the theory and practice of SVRG, Neurips 2019.
Preprint
Code
R. M. G. , D. Kovalev, F. Lieder, P. Richtárik.
RSN: Randomized Subspace Newton, Neurips 2019.
Preprint
R. M. G. , N. Loizou, X. Qian, A. Sailanbayev, E. Shulgin, P. Richtárik.
SGD: general analysis and improved rates, (extended oral presentation) ICML 2019.
Preprint
Proceedings
A. Bibi, A. Sailanbayev, B. Ghanem, R. M. G. and P. Richtárik.
Improving SAGA via a probabilistic interpolation with gradient descent, 2018.
Preprint
B. K. Abid and R. M. G. .
Greedy stochastic algorithms for entropy-regularized optimal transport problems, AISTATS, 2018.
Preprint
Proceedings
Poster
R. M. G. and P. Richtárik.
Randomized quasi-Newton updates are linearly convergent matrix inversion algorithms, SIAM Journal on Matrix Analysis and Applications, 2017.
Preprint
Code
Journal
Slides
R. M. G.
Sketch and Project: Randomized Iterative Methods for Linear Systems and Inverting Matrices, PhD Dissertation, School of Mathematics, The University of Edinburgh, 2016.
Preprint
Code
Slides
R. M. G. and M. P. Mello.
Computing the sparsity pattern of Hessians using automatic differentiation, ACM Transactions on Mathematical Software, 2014.
Preprint
Journal
Code
R. M. G. and M. P. Mello.
A new framework for Hessian automatic differentiation, Optimization Methods and Software, 2012.
Preprint
Journal
Code