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ORCIDDavid Martínez-Rubio
Person information
- affiliation: Zuse Institute Berlin (ZIB), Laboratory for Interactive Optimization and Learning, Germany
- affiliation: TU Berlin, Germany
- affiliation (former, PhD 2021): University of Oxford, Department of Computer Science, UK
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Conference and Workshop Papers
- 2024
[c9]David Martínez-Rubio, Christophe Roux, Sebastian Pokutta:
Convergence and Trade-Offs in Riemannian Gradient Descent and Riemannian Proximal Point. ICML 2024- 2023
- [c8]David Martínez-Rubio
, Sebastian Pokutta:
Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties. COLT 2023: 359-393 - [c7]David Martínez-Rubio, Elias Samuel Wirth, Sebastian Pokutta:
Accelerated and Sparse Algorithms for Approximate Personalized PageRank and Beyond. COLT 2023: 2852-2876 - [c6]Christopher Criscitiello, David Martínez-Rubio, Nicolas Boumal:
Open Problem: Polynomial linearly-convergent method for g-convex optimization? COLT 2023: 5950-5956 - 2022
- [c5]David Martínez-Rubio:
Global Riemannian Acceleration in Hyperbolic and Spherical Spaces. ALT 2022: 768-826 - [c4]Francisco Criado, David Martínez-Rubio, Sebastian Pokutta:
Fast Algorithms for Packing Proportional Fairness and its Dual. NeurIPS 2022 - 2019
- [c3]Mario Lezcano Casado, David Martínez-Rubio:
Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group. ICML 2019: 3794-3803 - [c2]David Martínez-Rubio, Varun Kanade, Patrick Rebeschini:
Decentralized Cooperative Stochastic Bandits. NeurIPS 2019: 4531-4542 - 2018
- [c1]Atilim Gunes Baydin, Robert Cornish, David Martínez-Rubio, Mark Schmidt, Frank Wood:
Online Learning Rate Adaptation with Hypergradient Descent. ICLR (Poster) 2018
Informal and Other Publications
- 2023
- [i8]David Martínez-Rubio, Christophe Roux, Christopher Criscitiello, Sebastian Pokutta:
Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties. CoRR abs/2305.16186 (2023) - [i7]Christopher Criscitiello, David Martínez-Rubio, Nicolas Boumal:
Open Problem: Polynomial linearly-convergent method for geodesically convex optimization? CoRR abs/2307.12743 (2023) - 2022
- [i6]David Martínez-Rubio, Sebastian Pokutta:
Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties. CoRR abs/2211.14645 (2022) - 2019
- [i5]Mario Lezcano Casado, David Martínez-Rubio:
Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group. CoRR abs/1901.08428 (2019) - [i4]Chris Mingard, Joar Skalse, Guillermo Valle Pérez, David Martínez-Rubio, Vladimir Mikulik, Ard A. Louis:
Neural networks are a priori biased towards Boolean functions with low entropy. CoRR abs/1909.11522 (2019) - 2018
- [i3]David Martínez-Rubio, Varun Kanade, Patrick Rebeschini:
Decentralized Cooperative Stochastic Multi-armed Bandits. CoRR abs/1810.04468 (2018) - 2017
- [i2]Atilim Gunes Baydin, Robert Cornish, David Martínez-Rubio, Mark Schmidt, Frank D. Wood:
Online Learning Rate Adaptation with Hypergradient Descent. CoRR abs/1703.04782 (2017) - [i1]Mario Lezcano Casado, Atilim Gunes Baydin, David Martínez-Rubio, Tuan Anh Le, Frank D. Wood, Lukas Heinrich, Gilles Louppe, Kyle Cranmer, Karen Ng, Wahid Bhimji, Prabhat:
Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators. CoRR abs/1712.07901 (2017)
Coauthor Index
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