Imagen de Portada

Middle-mile logistics through the lens of goal-conditioned reinforcement learning

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Eberhard, Onno, Cuvelier, Thibaut, Valko, Michal, De Backer, Bruno
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

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

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

Bandits on graphs and structures
por: Valko, Michal
Publicado: (2026)

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

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

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

Adaptive multi-fidelity optimization with fast learning rates
por: Fiegel, Come, et al.
Publicado: (2026)

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

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

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

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

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

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

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

Extreme bandits
por: Carpentier, Alexandra, et al.
Publicado: (2026)

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

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

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

Commit to the Bit: Reactive Reinforcement Learning Done Right
por: Eberhard, Onno, et al.
Publicado: (2026)

Partially Observable Reinforcement Learning with Memory Traces
por: Eberhard, Onno, et al.
Publicado: (2025)

Reward function compression facilitates goal-dependent reinforcement learning
por: Molinaro, Gaia, et al.
Publicado: (2025)

Generation through the lens of learning theory
por: Li, Jiaxun, et al.
Publicado: (2024)

Dynamic object goal pushing with mobile manipulators through model-free constrained reinforcement learning
por: Dadiotis, Ioannis, et al.
Publicado: (2025)

A Pontryagin Perspective on Reinforcement Learning
por: Eberhard, Onno, et al.
Publicado: (2024)

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

Bandits attack function optimization
por: Preux, Philippe, et al.
Publicado: (2026)

Stochastic simultaneous optimistic optimization
por: Valko, Michal, et al.
Publicado: (2026)

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

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

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

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

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

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

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

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

Controllability in preference-conditioned multi-objective reinforcement learning
por: Molins, Pau de las Heras, et al.
Publicado: (2026)

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

Spectral Thompson sampling
por: Kocak, Tomas, et al.
Publicado: (2026)

Sample Complexity Bounds for Stochastic Shortest Path with a Generative Model
por: Tarbouriech, Jean, et al.
Publicado: (2026)

Spectral bandits for smooth graph functions
por: Valko, Michal, et al.
Publicado: (2026)