Efficiently escaping saddle points on manifolds C Criscitiello, N Boumal Advances in Neural Information Processing Systems 32, 2019 | 72 | 2019 |
An accelerated first-order method for non-convex optimization on manifolds C Criscitiello, N Boumal Foundations of Computational Mathematics 23 (4), 1433-1509, 2023 | 34 | 2023 |
Negative curvature obstructs acceleration for strongly geodesically convex optimization, even with exact first-order oracles C Criscitiello, N Boumal Conference on Learning Theory, 496-542, 2022 | 23 | 2022 |
Curvature and complexity: Better lower bounds for geodesically convex optimization C Criscitiello, N Boumal The Thirty Sixth Annual Conference on Learning Theory, 2969-3013, 2023 | 6 | 2023 |
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 | 3* | 2023 |
Accelerated Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties D Martínez-Rubio, C Roux, C Criscitiello, S Pokutta Proceedings of Optimization for Machine Learning (NeurIPS Workshop OPT 2023), 2023 | 2* | 2023 |
Synchronization on circles and spheres with nonlinear interactions C Criscitiello, Q Rebjock, AD McRae, N Boumal arXiv preprint arXiv:2405.18273, 2024 | | 2024 |
Group ID U13785 Affiliated authors Boumal, Nicolas C Criscitiello, RA Dragomir, S Eggli, AD Mc Rae, AA Musat, Q Rebjock | | |