| Inexact coordinate descent: complexity and preconditioning R Tappenden, P Richtárik, J Gondzio Journal of Optimization Theory and Applications 170 (1), 144-176, 2016 | 96 | 2016 |
| A flexible coordinate descent method K Fountoulakis, R Tappenden Computational Optimization and Applications 70 (2), 351-394, 2018 | 39* | 2018 |
| On the complexity of parallel coordinate descent R Tappenden, M Takáč, P Richtárik Optimization Methods and Software 33 (2), 372-395, 2018 | 38 | 2018 |
| Separable approximations and decomposition methods for the augmented Lagrangian R Tappenden, P Richtárik, B Büke Optimization Methods and Software 30 (3), 643-668, 2015 | 36 | 2015 |
| A flexible ADMM algorithm for big data applications DP Robinson, R Tappenden Journal of Scientific Computing 71 (1), 435-467, 2017 | 24 | 2017 |
| Preliminary experimental results from a MARS micro-CT system P He, H Yu, P Thayer, X Jin, Q Xu, J Bennett, R Tappenden, B Wei, ... Journal of X-ray Science and Technology 20 (2), 199-211, 2012 | 21 | 2012 |
| Decentralized personalized federated learning: Lower bounds and optimal algorithm for all personalization modes A Sadiev, E Borodich, A Beznosikov, D Dvinskikh, S Chezhegov, ... EURO Journal on Computational Optimization 10, 100041, 2022 | 19 | 2022 |
| Linear Convergence of Randomized Feasible Descent Methods Under the Weak Strong Convexity Assumption C Ma, R Tappenden, M Takác Journal of Machine Learning Research 17 (230), 1-24, 2016 | 19 | 2016 |
| Fast and safe: accelerated gradient methods with optimality certificates and underestimate sequences M Jahani, NVC Gudapati, C Ma, R Tappenden, M Takáč Computational Optimization and Applications 79 (2), 369-404, 2021 | 16* | 2021 |
| Determinant and exchange algorithms for observation subset selection R Broughton, I Coope, P Renaud, R Tappenden IEEE Transactions on Image Processing 19 (9), 2437-2443, 2010 | 16 | 2010 |
| FLECS: A Federated Learning Second-Order Framework via Compression and Sketching A Agafonov, D Kamzolov, R Tappenden, A Gasnikov, M Takáč arXiv preprint arXiv:2206.02009, 2022 | 13 | 2022 |
| Efficient calculation of regular simplex gradients I Coope, R Tappenden Computational Optimization and Applications 72 (3), 561-588, 2019 | 13 | 2019 |
| Sonia: A symmetric blockwise truncated optimization algorithm M Jahani, M Nazari, R Tappenden, A Berahas, M Takác International Conference on Artificial Intelligence and Statistics, 487-495, 2021 | 12 | 2021 |
| A box constrained gradient projection algorithm for compressed sensing RL Broughton, ID Coope, PF Renaud, REH Tappenden Signal Processing 91 (8), 1985-1992, 2011 | 12 | 2011 |
| Stochastic gradient methods with preconditioned updates A Sadiev, A Beznosikov, AJ Almansoori, D Kamzolov, R Tappenden, ... Journal of Optimization Theory and Applications, 1-19, 2024 | 9 | 2024 |
| Gradient and diagonal Hessian approximations using quadratic interpolation models and aligned regular bases ID Coope, R Tappenden Numerical Algorithms 88 (2), 767-791, 2021 | 8* | 2021 |
| Dual Free Adaptive Minibatch SDCA for Empirical Risk Minimization X He, R Tappenden, M Takac Frontiers in Applied Mathematics and Statistics 4, 33, 2018 | 5 | 2018 |
| Domain specific transfer learning using image mixing and stochastic image selection S Coup, V Vetrova, E Frank, R Tappenden The Sixth Workshop on Fine-Grained Visual Categorization (FGVC6), Computer …, 2019 | 1 | 2019 |
| X-ray image enhancement via determinant based feature selection R Tappenden, J Hegarty, R Broughton, A Butler, I Coope, P Renaud Australasian Physical & Engineering Sciences in Medicine 36 (4), 449-455, 2013 | 1 | 2013 |
| A Study on Monthly Marine Heatwave Forecasts in New Zealand: An Investigation of Imbalanced Regression Loss Functions with Neural Network Models D Ning, V Vetrova, S Delaux, R Tappenden, KR Bryan, YS Koh arXiv preprint arXiv:2502.13495, 2025 | | 2025 |
Martin TakáčMohamed bin Zayed University of Artificial Intelligence (MBZUAI)כתובת אימייל מאומתת בדומיין mbzuai.ac.ae