David Martínez-Rubio

31 papers A* 10A 2B 1Journal 17Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Complexity of Classical Acceleration for ℓ
CoRR
Kimon Fountoulakis, David Martínez-Rubio
2025 A conf
Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties.
AISTATS
David Martínez-Rubio, Christophe Roux, Christopher Criscitiello, Sebastian Pokutta
2025 J jnl
Beyond Short Steps in Frank-Wolfe Algorithms.
CoRR
David Martínez-Rubio, Sebastian Pokutta
2025 A conf
Black-Box Uniform Stability for Non-Euclidean Empirical Risk Minimization.
AISTATS
Simon Vary, David Martínez-Rubio, Patrick Rebeschini
2025 A* conf
Implicit Riemannian Optimism with Applications to Min-Max Problems.
ICML
Christophe Roux, David Martínez-Rubio, Sebastian Pokutta
2025 J jnl
Implicit Riemannian Optimism with Applications to Min-Max Problems.
CoRR
Christophe Roux, David Martínez-Rubio, Sebastian Pokutta
2025 J jnl
Linear Convergence of the Frank-Wolfe Algorithm over Product Polytopes.
CoRR
Gabriele Iommazzo, David Martínez-Rubio, Francisco Criado, Elias Samuel Wirth, Sebastian Pokutta
2025 J jnl
Neural Sum-of-Squares: Certifying the Nonnegativity of Polynomials with Transformers.
CoRR
Nico Pelleriti, Christoph Spiegel, Shiwei Liu, David Martínez-Rubio, Max Zimmer, Sebastian Pokutta
2025 A* conf
Non-Euclidean High-Order Smooth Convex Optimization Extended Abstract.
COLT
Juan Pablo Contreras, Cristóbal Guzmán, David Martínez-Rubio
2025 J jnl
On the necessity of adaptive regularisation:Optimal anytime online learning on ℓ
CoRR
Emmeran Johnson, David Martínez-Rubio, Ciara Pike-Burke, Patrick Rebeschini
2025 A* conf
Secant Line Search for Frank-Wolfe Algorithms.
ICML
Deborah Hendrych, Sebastian Pokutta, Mathieu Besançon, David Martínez-Rubio
2025 J jnl
Smooth Quasar-Convex Optimization with Constraints.
CoRR
David Martínez-Rubio
2024 J jnl
Black-Box Uniform Stability for Non-Euclidean Empirical Risk Minimization.
CoRR
Simon Vary, David Martínez-Rubio, Patrick Rebeschini
2024 A* conf
Convergence and Trade-Offs in Riemannian Gradient Descent and Riemannian Proximal Point.
ICML
David Martínez-Rubio, Christophe Roux, Sebastian Pokutta
2024 J jnl
Non-Euclidean High-Order Smooth Convex Optimization.
CoRR
Juan Pablo Contreras, Cristóbal Guzmán, David Martínez-Rubio
2023 J jnl
Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties.
CoRR
David Martínez-Rubio, Christophe Roux, Christopher Criscitiello, Sebastian Pokutta
2023 A* conf
Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties.
COLT
David Martínez-Rubio, Sebastian Pokutta
2023 A* conf
Accelerated and Sparse Algorithms for Approximate Personalized PageRank and Beyond.
COLT
David Martínez-Rubio, Elias Samuel Wirth, Sebastian Pokutta
2023 A* conf
Open Problem: Polynomial linearly-convergent method for g-convex optimization?
COLT
Christopher Criscitiello, David Martínez-Rubio, Nicolas Boumal
2023 J jnl
Open Problem: Polynomial linearly-convergent method for geodesically convex optimization?
CoRR
Christopher Criscitiello, David Martínez-Rubio, Nicolas Boumal
2022 J jnl
Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties.
CoRR
David Martínez-Rubio, Sebastian Pokutta
2022 A* conf
Fast Algorithms for Packing Proportional Fairness and its Dual.
NeurIPS
Francisco Criado, David Martínez-Rubio, Sebastian Pokutta
2022 B conf
Global Riemannian Acceleration in Hyperbolic and Spherical Spaces.
ALT
David Martínez-Rubio
2019 A* conf
Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group.
ICML
Mario Lezcano Casado, David Martínez-Rubio
2019 J jnl
Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group.
CoRR
Mario Lezcano Casado, David Martínez-Rubio
2019 A* conf
Decentralized Cooperative Stochastic Bandits.
NeurIPS
David Martínez-Rubio, Varun Kanade, Patrick Rebeschini
2019 J jnl
Neural networks are a priori biased towards Boolean functions with low entropy.
CoRR
Chris Mingard, Joar Skalse, Guillermo Valle Pérez, David Martínez-Rubio, Vladimir Mikulik, Ard A. Louis
2018 J jnl
Decentralized Cooperative Stochastic Multi-armed Bandits.
CoRR
David Martínez-Rubio, Varun Kanade, Patrick Rebeschini
2018 — conf
Online Learning Rate Adaptation with Hypergradient Descent.
ICLR (Poster)
Atilim Gunes Baydin, Robert Cornish, David Martínez-Rubio, Mark Schmidt, Frank Wood
2017 J jnl
Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators.
CoRR
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
2017 J jnl
Online Learning Rate Adaptation with Hypergradient Descent.
CoRR
Atilim Gunes Baydin, Robert Cornish, David Martínez-Rubio, Mark Schmidt, Frank D. Wood