Cover Image

Adaptive multi-fidelity optimization with fast learning rates

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Fiegel, Come, Gabillon, Victor, Valko, Michal
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Optimal last-iterate convergence in matrix games with bandit feedback using the log-barrier
by: Fiegel, Come, et al.
Published: (2026)

The Harder Path: Last Iterate Convergence for Uncoupled Learning in Zero-Sum Games with Bandit Feedback
by: Fiegel, Côme, et al.
Published: (2026)

Scale-free adaptive planning for deterministic dynamics & discounted rewards
by: Bartlett, Peter L., et al.
Published: (2026)

Adaptive graph-based algorithms for conditional anomaly detection and semi-supervised learning
by: Valko, Michal
Published: (2026)

Best of both worlds: Stochastic & adversarial best-arm identification
by: Abbasi-Yadkori, Yasin, et al.
Published: (2026)

Pack only the essentials: Adaptive dictionary learning for kernel ridge regression
by: Calandriello, Daniele, et al.
Published: (2026)

Online combinatorial optimization with stochastic decision sets and adversarial losses
by: Neu, Gergely, et al.
Published: (2026)

Distance metric learning for conditional anomaly detection
by: Valko, Michal, et al.
Published: (2026)

Learning to Allocate Resources with Censored Feedback
by: Montanari, Giovanni, et al.
Published: (2026)

Bandits attack function optimization
by: Preux, Philippe, et al.
Published: (2026)

Stochastic simultaneous optimistic optimization
by: Valko, Michal, et al.
Published: (2026)

Bandits on graphs and structures
by: Valko, Michal
Published: (2026)

Online learning with noisy side observations
by: Kocák, Tomáš, et al.
Published: (2026)

Online learning with Erdős-Rényi side-observation graphs
by: Kocák, Tomáš, et al.
Published: (2026)

Black-box optimization of noisy functions with unknown smoothness
by: Grill, Jean-Bastien, et al.
Published: (2026)

Large-scale semi-supervised learning with online spectral graph sparsification
by: Calandriello, Daniele, et al.
Published: (2026)

VA-learning as a more efficient alternative to Q-learning
by: Tang, Yunhao, et al.
Published: (2023)

Feature importance analysis for patient management decisions
by: Valko, Michal, et al.
Published: (2026)

Learning from a single labeled face and a stream of unlabeled data
by: Kveton, Branislav, et al.
Published: (2026)

Revealing graph bandits for maximizing local influence
by: Carpentier, Alexandra, et al.
Published: (2026)

Extreme bandits
by: Carpentier, Alexandra, et al.
Published: (2026)

Semi-supervised learning with max-margin graph cuts
by: Kveton, Branislav, et al.
Published: (2026)

Efficient learning by implicit exploration in bandit problems with side observations
by: Kocak, Tomas, et al.
Published: (2026)

Improved large-scale graph learning through ridge spectral sparsification
by: Calandriello, Daniele, et al.
Published: (2026)

Online semi-supervised perception: Real-time learning without explicit feedback
by: Kveton, Branislav, et al.
Published: (2026)

Middle-mile logistics through the lens of goal-conditioned reinforcement learning
by: Eberhard, Onno, et al.
Published: (2026)

Trading off rewards and errors in multi-armed bandits
by: Erraqabi, Akram, et al.
Published: (2026)

Active multiple matrix completion with adaptive confidence sets
by: Locatelli, Andrea, et al.
Published: (2026)

Analysis of Nystrom method with sequential ridge leverage scores
by: Calandriello, Daniele, et al.
Published: (2026)

Bayesian policy gradient and actor-critic algorithms
by: Ghavamzadeh, Mohammad, et al.
Published: (2026)

Covariance-adapting algorithm for semi-bandits with application to sparse rewards
by: Perrault, Pierre, et al.
Published: (2026)

Learning predictive models for combinations of heterogeneous proteomic data sources
by: Valko, Michal, et al.
Published: (2026)

Language Generation with Replay: A Learning-Theoretic View of Model Collapse
by: Racca, Giorgio, et al.
Published: (2026)

Constrained multi-fidelity Bayesian optimization with automatic stop condition
by: Foumani, Zahra Zanjani, et al.
Published: (2025)

Progressive multi-fidelity learning with neural networks for physical system predictions
by: Conti, Paolo, et al.
Published: (2025)

Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning
by: Grill, Jean-Bastien, et al.
Published: (2026)

On two ways to use determinantal point processes for Monte Carlo integration
by: Gautier, Guillaume, et al.
Published: (2026)

Practical multi-fidelity machine learning: fusion of deterministic and Bayesian models
by: Yi, Jiaxiang, et al.
Published: (2024)

Adaptive multi-gradient methods for quasiconvex vector optimization and applications to multi-task learning
by: Minh, Nguyen Anh, et al.
Published: (2024)

Maximum Entropy Semi-Supervised Inverse Reinforcement Learning
by: Audiffren, Julien, et al.
Published: (2026)