| Online learning rate adaptation with hypergradient descent AG Baydin, R Cornish, DM Rubio, M Schmidt, F Wood arXiv preprint arXiv:1703.04782, 2017 | 296 | 2017 |
| Cheap orthogonal constraints in neural networks: A simple parametrization of the orthogonal and unitary group M Lezcano-Casado, D Martınez-Rubio International Conference on Machine Learning, 3794-3803, 2019 | 247 | 2019 |
| Decentralized cooperative stochastic bandits D Martínez-Rubio, V Kanade, P Rebeschini Advances in Neural Information Processing Systems 32, 2019 | 142 | 2019 |
| Neural networks are a priori biased towards boolean functions with low entropy C Mingard, J Skalse, G Valle-Pérez, D Martínez-Rubio, V Mikulik, ... arXiv preprint arXiv:1909.11522, 2019 | 35 | 2019 |
| Global Riemannian acceleration in hyperbolic and spherical spaces D Martínez-Rubio International Conference on Algorithmic Learning Theory, 768-826, 2022 | 25* | 2022 |
| Convergence analysis of an adaptive method of gradient descent DM Rubio University of Oxford, Oxford, M. Sc. thesis, 2017 | 20 | 2017 |
| Improvements to inference compilation for probabilistic programming in large-scale scientific simulators ML Casado, AG Baydin, DM Rubio, TA Le, F Wood, L Heinrich, G Louppe, ... arXiv preprint arXiv:1712.07901, 2017 | 11* | 2017 |
| Accelerated riemannian optimization: Handling constraints with a prox to bound geometric penalties D Martínez-Rubio, S Pokutta The Thirty Sixth Annual Conference on Learning Theory, 359-393, 2023 | 8 | 2023 |
| Accelerated and sparse algorithms for approximate personalized pagerank and beyond D Martínez-Rubio, E Wirth, S Pokutta The Thirty Sixth Annual Conference on Learning Theory, 2852-2876, 2023 | 7 | 2023 |
| Accelerated methods for riemannian min-max optimization ensuring bounded geometric penalties D Martínez-Rubio, C Roux, C Criscitiello, S Pokutta arXiv preprint arXiv:2305.16186, 2023 | 5 | 2023 |
| Fast algorithms for packing proportional fairness and its dual F Criado, D Martínez-Rubio, S Pokutta Advances in Neural Information Processing Systems 35, 25754-25766, 2022 | 5 | 2022 |
| Open Problem: Polynomial linearly-convergent method for g-convex optimization? C Criscitiello, D Martínez-Rubio, N Boumal The Thirty Sixth Annual Conference on Learning Theory, 5950-5956, 2023 | 2* | 2023 |
| Acceleration in first-order optimization methods: promenading beyond convexity or smoothness, and applications D Martínez-Rubio PQDT-Global, 2021 | 2 | 2021 |
| Beyond Short Steps in Frank-Wolfe Algorithms D Martínez-Rubio, S Pokutta arXiv preprint arXiv:2501.18773, 2025 | | 2025 |
| Secant Line Search for Frank-Wolfe Algorithms D Hendrych, M Besançon, D Martínez-Rubio, S Pokutta arXiv preprint arXiv:2501.18775, 2025 | | 2025 |
| Implicit Riemannian Optimism with Applications to Min-Max Problems C Roux, D Martínez-Rubio, S Pokutta arXiv preprint arXiv:2501.18381, 2025 | | 2025 |
| Black-Box Uniform Stability for Non-Euclidean Empirical Risk Minimization S Vary, D Martínez-Rubio, P Rebeschini arXiv preprint arXiv:2412.15956, 2024 | | 2024 |
| Non-Euclidean High-Order Smooth Convex Optimization JP Contreras, C Guzmán, D Martínez-Rubio arXiv preprint arXiv:2411.08987, 2024 | | 2024 |
| Convergence and trade-offs in Riemannian gradient descent and Riemannian proximal point D Martínez-Rubio, C Roux, S Pokutta arXiv preprint arXiv:2403.10429, 2024 | | 2024 |
| Characterization and computation of the Galois group of polynomials of degree 7 DM Rubio Universidad Complutense de Madrid, 2016 | | 2016 |