Image de couverture de livre

From Theory to Practice with RAVEN-UCB: Addressing Non-Stationarity in Multi-Armed Bandits through Variance Adaptation

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Fang, Junyi, Chen, Yuxun, Chen, Yuxin, Zhang, Chen
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning I.2.6; I.2.8; G.3
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
par: Yousaf, Iqra
Publié: (2024)

From Cumulative Constraints to Adaptive Runtime Safety Control for Nonstationary Reinforcement Learning
par: Tomashevskiy, Timofey
Publié: (2026)

From Next Token Prediction to (STRIPS) World Models
par: Núñez-Molina, Carlos, et autres
Publié: (2025)

Sketch Decompositions for Classical Planning via Deep Reinforcement Learning
par: Aichmüller, Michael, et autres
Publié: (2024)

LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction
par: George, Robert Joseph, et autres
Publié: (2025)

Zero-Shot Context Generalization in Reinforcement Learning from Few Training Contexts
par: Chapman, James, et autres
Publié: (2025)

FlowRL: Flow-Augmented Few-Shot Reinforcement Learning for Semi-Structured Sensor Data
par: Pivezhandi, Mohammad, et autres
Publié: (2024)

A Parallel Hybrid Action Space Reinforcement Learning Model for Real-world Adaptive Traffic Signal Control
par: Wang, Yuxuan, et autres
Publié: (2025)

Predicting and improving test-time scaling laws via reward tail-guided search
par: Li, Muheng, et autres
Publié: (2026)

NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning Problems
par: Núñez-Molina, Carlos, et autres
Publié: (2023)

Constrained Auto-Bidding via Generative Response Modeling
par: Yang, Eunseok, et autres
Publié: (2026)

Fractional Policy Gradients: Reinforcement Learning with Long-Term Memory
par: Pawar, Urvi, et autres
Publié: (2025)

Learning to Select Goals in Automated Planning with Deep-Q Learning
par: Núñez-Molina, Carlos, et autres
Publié: (2024)

Are We Winning the Wrong Game? Revisiting Evaluation Practices for Long-Term Time Series Forecasting
par: Phungtua-eng, Thanapol, et autres
Publié: (2026)

Selective Progress-Aware Querying for Human-in-the-Loop Reinforcement Learning
par: Muraleedharan, Anujith, et autres
Publié: (2025)

Evolving machine learning workflows through interactive AutoML
par: Barbudo, Rafael, et autres
Publié: (2024)

The Final-Stage Bottleneck: A Systematic Dissection of the R-Learner for Network Causal Inference
par: Sairam, S, et autres
Publié: (2025)

SCULPT: Constraint-Guided Pruned MCTS that Carves Efficient Paths for Mathematical Reasoning
par: Fang, Qitong, et autres
Publié: (2026)

PIRS: Physics-Informed Reward Shaping for SAC-Based Building Energy Management
par: Zaregarizi, Shadmehr, et autres
Publié: (2026)

PillagerBench: Benchmarking LLM-Based Agents in Competitive Minecraft Team Environments
par: Schipper, Olivier, et autres
Publié: (2025)

Improving Industrial Injection Molding Processes with Explainable AI for Quality Classification
par: Rottenwalter, Georg, et autres
Publié: (2025)

Novel Approaches to Artificial Intelligence Development Based on the Nearest Neighbor Method
par: Priezzhev, I. I., et autres
Publié: (2025)

Advancements in synthetic data extraction for industrial injection molding
par: Rottenwalter, Georg, et autres
Publié: (2025)

Predicting Future Actions of Reinforcement Learning Agents
par: Chung, Stephen, et autres
Publié: (2024)

Scaling Trends for Multi-Hop Contextual Reasoning in Mid-Scale Language Models
par: Steele, Brady, et autres
Publié: (2026)

Learning Natural Language Constraints for Safe Reinforcement Learning of Language Agents
par: Chua, Jaymari, et autres
Publié: (2025)

The Reality Gap in Robotics: Challenges, Solutions, and Best Practices
par: Aljalbout, Elie, et autres
Publié: (2025)

From Demonstrations to Safe Deployment: Path-Consistent Safety Filtering for Diffusion Policies
par: Römer, Ralf, et autres
Publié: (2025)

Towards Systematic Generalization for Power Grid Optimization Problems
par: Memon, Zeeshan, et autres
Publié: (2026)

Machine Learning Based Path Planning for Improved Rover Navigation (Pre-Print Version)
par: Abcouwer, Neil, et autres
Publié: (2020)

Foundational Requirements for Artificial General Intelligence: A Falsifiable Framework Based on Signal Prediction
par: Šprogar, Matej
Publié: (2025)

COMET: Codebook-based Online-adaptive Multi-scale Embedding for Time-series Anomaly Detection
par: Park, Jinwoo, et autres
Publié: (2026)

Sim-to-reality adaptation for Deep Reinforcement Learning applied to an underwater docking application
par: Chaarani, Alaaeddine, et autres
Publié: (2026)

StepScorer: Accelerating Reinforcement Learning with Step-wise Scoring and Psychological Regret Modeling
par: Xu, Zhe
Publié: (2026)

The CRITICAL Records Integrated Standardization Pipeline (CRISP): End-to-End Processing of Large-scale Multi-institutional OMOP CDM Data
par: Luo, Xiaolong, et autres
Publié: (2025)

N-Agent Ad Hoc Teamwork
par: Wang, Caroline, et autres
Publié: (2024)

Deep Reinforcement Learning for Day-to-day Dynamic Tolling in Tradable Credit Schemes
par: Wu, Xiaoyi, et autres
Publié: (2025)

APC-GNN++: An Adaptive Patient-Centric GNN with Context-Aware Attention and Mini-Graph Explainability for Diabetes Classification
par: Berkani, Khaled
Publié: (2025)

Bilinear Mamba-Koopman Neural MPC for Varying Dynamics
par: Pagi, Matan, et autres
Publié: (2026)

Differentiable Symbolic Planning: A Neural Architecture for Constraint Reasoning with Learned Feasibility
par: Oruganti, Venkatakrishna Reddy
Publié: (2026)