Imagen de Portada

Tree Ensembles for Contextual Bandits

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Nilsson, Hannes, Johansson, Rikard, Åkerblom, Niklas, Chehreghani, Morteza Haghir
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Bayesian Analysis of Combinatorial Gaussian Process Bandits
por: Sandberg, Jack, et al.
Publicado: (2023)

Cost-Efficient Online Decision Making: A Combinatorial Multi-Armed Bandit Approach
por: Rahbar, Arman, et al.
Publicado: (2023)

Shift of Pairwise Similarities for Data Clustering
por: Chehreghani, Morteza Haghir
Publicado: (2021)

Passive and Active Learning of Driver Behavior from Electric Vehicles
por: Comuni, Federica, et al.
Publicado: (2022)

An Efficient Local Search Approach for Polarized Community Discovery in Signed Networks
por: Aronsson, Linus, et al.
Publicado: (2025)

On the Complexity of Optimal Graph Rewiring for Oversmoothing and Oversquashing in Graph Neural Networks
por: Chehreghani, Mostafa Haghir
Publicado: (2026)

Two-Stage Learned Decomposition for Scalable Routing on Multigraphs
por: Rydin, Filip, et al.
Publicado: (2026)

Tactical Decision Making for Autonomous Trucks by Deep Reinforcement Learning with Total Cost of Operation Based Reward
por: Pathare, Deepthi, et al.
Publicado: (2024)

Hierarchical Correlation Clustering and Tree Preserving Embedding
por: Chehreghani, Morteza Haghir, et al.
Publicado: (2020)

Multi-Objective Reinforcement Learning for Tactical Decision Making for Trucks in Highway Traffic
por: Pathare, Deepthi, et al.
Publicado: (2026)

Online Learning Models for Vehicle Usage Prediction During COVID-19
por: Lindroth, Tobias, et al.
Publicado: (2022)

Cold-Start Active Correlation Clustering
por: Aronsson, Linus, et al.
Publicado: (2025)

Adaptive Prior Selection in Gaussian Process Bandits with Thompson Sampling
por: Sandberg, Jack, et al.
Publicado: (2025)

A Benchmark Dataset for Graph Regression with Homogeneous and Multi-Relational Variants
por: Samoaa, Peter, et al.
Publicado: (2025)

Graph Neural Networks in Multi-Omics Cancer Research: A Structured Survey
por: Zohari, Payam, et al.
Publicado: (2025)

Analysing the Behaviour of Tree-Based Neural Networks in Regression Tasks
por: Samoaa, Peter, et al.
Publicado: (2024)

Less Is More -- On the Importance of Sparsification for Transformers and Graph Neural Networks for TSP
por: Lischka, Attila, et al.
Publicado: (2024)

A GREAT Architecture for Edge-Based Graph Problems Like TSP
por: Lischka, Attila, et al.
Publicado: (2024)

Beyond Simple Graphs: Neural Multi-Objective Routing on Multigraphs
por: Rydin, Filip, et al.
Publicado: (2025)

AFABench: A Generic Framework for Benchmarking Active Feature Acquisition
por: Schütz, Valter, et al.
Publicado: (2025)

Strong Transitivity Relations and Graph Neural Networks
por: Mohamadi, Yassin, et al.
Publicado: (2024)

Anchor-based oversampling for imbalanced tabular data via contrastive and adversarial learning
por: Mohammadi, Hadi, et al.
Publicado: (2025)

Neighborhood-Order Learning Graph Attention Network for Fake News Detection
por: Lakzaei, Batool, et al.
Publicado: (2025)

LOSS-GAT: Label Propagation and One-Class Semi-Supervised Graph Attention Network for Fake News Detection
por: Lakzaei, Batool, et al.
Publicado: (2024)

A Decision-Based Heterogenous Graph Attention Network for Multi-Class Fake News Detection
por: Lakzaei, Batool, et al.
Publicado: (2025)

Information-Theoretic Active Correlation Clustering
por: Aronsson, Linus, et al.
Publicado: (2024)

Non-Myopic Active Feature Acquisition via Pathwise Policy Gradients
por: Aronsson, Linus, et al.
Publicado: (2026)

Correlation Clustering with Active Learning of Pairwise Similarities
por: Aronsson, Linus, et al.
Publicado: (2023)

Provable Anytime Ensemble Sampling Algorithms in Nonlinear Contextual Bandits
por: Sun, Jiazheng, et al.
Publicado: (2025)

Content Augmented Graph Neural Networks
por: Nasrabadi, Fatemeh Gholamzadeh, et al.
Publicado: (2023)

A Survey on Active Feature Acquisition Strategies
por: Aronsson, Linus, et al.
Publicado: (2025)

Autonomous Drug Design with Multi-Armed Bandits
por: Svensson, Hampus Gummesson, et al.
Publicado: (2022)

Decoupling Task and Behavior: A Two-Stage Reward Curriculum in Reinforcement Learning for Robotics
por: Freitag, Kilian, et al.
Publicado: (2026)

Efficient Online Decision Tree Learning with Active Feature Acquisition
por: Rahbar, Arman, et al.
Publicado: (2023)

Causal Contextual Bandits with Adaptive Context
por: Madhavan, Rahul, et al.
Publicado: (2024)

Diffusion Models Meet Contextual Bandits
por: Aouali, Imad
Publicado: (2024)

Learning When to Trust in Contextual Bandits
por: Ghasemi, Majid, et al.
Publicado: (2026)

A Contextual Combinatorial Bandit Approach to Negotiation
por: Li, Yexin, et al.
Publicado: (2024)

Federated Linear Contextual Bandits with Heterogeneous Clients
por: Blaser, Ethan, et al.
Publicado: (2024)

Conservative Contextual Bandits: Beyond Linear Representations
por: Deb, Rohan, et al.
Publicado: (2024)