Filip Hanzely
Filip Hanzely
PhD student, KAUST
確認したメール アドレス: kaust.edu.sa - ホームページ
タイトル引用先
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
92018
Accelerated Bregman proximal gradient methods for relatively smooth convex optimization
F Hanzely, P Richtarik, L Xiao
arXiv preprint arXiv:1808.03045, 2018
82018
Privacy preserving randomized gossip algorithms
F Hanzely, J Konečný, N Loizou, P Richtárik, D Grishchenko
arXiv preprint arXiv:1706.07636, 2017
82017
Accelerated coordinate descent with arbitrary sampling and best rates for minibatches
F Hanzely, P Richtárik
arXiv preprint arXiv:1809.09354, 2018
72018
Fastest rates for stochastic mirror descent methods
F Hanzely, P Richtárik
arXiv preprint arXiv:1803.07374, 2018
52018
Testing for causality in reconstructed state spaces by an optimized mixed prediction method
A Krakovská, F Hanzely
Physical Review E 94 (5), 052203, 2016
52016
SEGA: Variance Reduction via Gradient Sketching
F Hanzely, K Mishchenko, P Richtárik
Advances in Neural Information Processing Systems, 2082-2093, 2018
42018
99% of Parallel Optimization is Inevitably a Waste of Time
K Mishchenko, F Hanzely, P Richtárik
arXiv preprint arXiv:1901.09437, 2019
32019
A privacy preserving randomized gossip algorithm via controlled noise insertion
F Hanzely, J Konečný, N Loizou, P Richtárik, D Grishchenko
arXiv preprint arXiv:1901.09367, 2019
12019
A nonconvex projection method for robust pca
A Dutta, F Hanzely, P Richtárik
arXiv preprint arXiv:1805.07962, 2018
12018
A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate Descent
E Gorbunov, F Hanzely, P Richtárik
arXiv preprint arXiv:1905.11261, 2019
2019
One Method to Rule Them All: Variance Reduction for Data, Parameters and Many New Methods
F Hanzely, P Richtárik
arXiv preprint arXiv:1905.11266, 2019
2019
Best Pair Formulation & Accelerated Scheme for Non-convex Principal Component Pursuit
A Dutta, F Hanzely, J Liang, P Richtárik
arXiv preprint arXiv:1905.10598, 2019
2019
Extending the Reach of Big Data Optimization-Randomized Algorithms for Minimizing Relatively Smooth Functions
F Hanzely, P Richtárik
2018
Accelerated Stochastic Matrix Inversion
RM Gower, F Hanzely, P Richtárik, SU Stich
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