A Modularized Framework for Piecewise-Stationary Restless Bandits
Fuente:
arXiv
Saved in:
| Main Authors: | Li, Kuan-Ta, Lin, Chia-Chun, Hsieh, Ping-Chun, Huang, Yu-Chih |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Diminishing Exploration: A Minimalist Approach to Piecewise Stationary Multi-Armed Bandits
by: Li, Kuan-Ta, et al.
Published: (2024)
by: Li, Kuan-Ta, et al.
Published: (2024)
Non-Stationary Restless Multi-Armed Bandits with Provable Guarantee
by: Hung, Yu-Heng, et al.
Published: (2025)
by: Hung, Yu-Heng, et al.
Published: (2025)
Restless Linear Bandits
by: Khaleghi, Azadeh
Published: (2024)
by: Khaleghi, Azadeh
Published: (2024)
Almost Minimax Optimal Best Arm Identification in Piecewise Stationary Linear Bandits
by: Hou, Yunlong, et al.
Published: (2024)
by: Hou, Yunlong, et al.
Published: (2024)
Optimal Best Arm Identification with Fixed Confidence in Restless Bandits
by: Karthik, P. N., et al.
Published: (2023)
by: Karthik, P. N., et al.
Published: (2023)
On optimal solutions of classical and sliced Wasserstein GANs with non-Gaussian data
by: Huang, Yu-Jui, et al.
Published: (2025)
by: Huang, Yu-Jui, et al.
Published: (2025)
Sequential Change Detection for Learning in Piecewise Stationary Bandit Environments
by: Huang, Yu-Han, et al.
Published: (2025)
by: Huang, Yu-Han, et al.
Published: (2025)
Detection Augmented Bandit Procedures for Piecewise Stationary MABs: A Modular Approach
by: Huang, Yu-Han, et al.
Published: (2025)
by: Huang, Yu-Han, et al.
Published: (2025)
The Geometric Cost of Normalization: Affine Bounds on the Bayesian Complexity of Neural Networks
by: Chun, Sungbae
Published: (2026)
by: Chun, Sungbae
Published: (2026)
eOptShrinkQ: Near-Lossless KV Cache Compression Through Optimal Spectral Denoising and Quantization
by: Su, Pei-Chun
Published: (2026)
by: Su, Pei-Chun
Published: (2026)
Regret Bounds for Noise-Free Cascaded Kernelized Bandits
by: Li, Zihan, et al.
Published: (2022)
by: Li, Zihan, et al.
Published: (2022)
Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability
by: Chen, Fan, et al.
Published: (2024)
by: Chen, Fan, et al.
Published: (2024)
Optimal Clustering with Bandit Feedback
by: Yang, Junwen, et al.
Published: (2022)
by: Yang, Junwen, et al.
Published: (2022)
Batched Kernelized Bandits: Refinements and Extensions
by: Ma, Chenkai, et al.
Published: (2026)
by: Ma, Chenkai, et al.
Published: (2026)
Bandit Convex Optimization with Gradient Prediction Adaptivity
by: Wang, Shuche, et al.
Published: (2026)
by: Wang, Shuche, et al.
Published: (2026)
Optimal Arm Elimination Algorithms for Combinatorial Bandits
by: Wen, Yuxiao, et al.
Published: (2025)
by: Wen, Yuxiao, et al.
Published: (2025)
Lower Bounds for Time-Varying Kernelized Bandits
by: Cai, Xu, et al.
Published: (2024)
by: Cai, Xu, et al.
Published: (2024)
Conversational Dueling Bandits in Generalized Linear Models
by: Yang, Shuhua, et al.
Published: (2024)
by: Yang, Shuhua, et al.
Published: (2024)
Predictability Analysis of Regression Problems via Conditional Entropy Estimations
by: Fang, Yu-Hsueh, et al.
Published: (2024)
by: Fang, Yu-Hsueh, et al.
Published: (2024)
Beyond Freshness and Semantics: A Coupon-Collector Framework for Effective Status Updates
by: Ahmed, Youssef, et al.
Published: (2026)
by: Ahmed, Youssef, et al.
Published: (2026)
Competing Bandits in Matching Markets via Super Stability
by: Basu, Soumya
Published: (2025)
by: Basu, Soumya
Published: (2025)
Quantile Multi-Armed Bandits with 1-bit Feedback
by: Lau, Ivan, et al.
Published: (2025)
by: Lau, Ivan, et al.
Published: (2025)
Online Clustering of Data Sequences with Bandit Information
by: Chandran, G Dhinesh, et al.
Published: (2025)
by: Chandran, G Dhinesh, et al.
Published: (2025)
A General Framework for Clustering and Distribution Matching with Bandit Feedback
by: Yavas, Recep Can, et al.
Published: (2024)
by: Yavas, Recep Can, et al.
Published: (2024)
Quantum-Enhanced Neural Contextual Bandit Algorithms
by: Huang, Yuqi, et al.
Published: (2026)
by: Huang, Yuqi, et al.
Published: (2026)
Regret Tail Characterization of Optimal Bandit Algorithms with Generic Rewards
by: Panda, Subhodip, et al.
Published: (2026)
by: Panda, Subhodip, et al.
Published: (2026)
Improved Regret Bounds for Linear Bandits with Heavy-Tailed Rewards
by: Tajdini, Artin, et al.
Published: (2025)
by: Tajdini, Artin, et al.
Published: (2025)
Indexed Minimum Empirical Divergence-Based Algorithms for Linear Bandits
by: Bian, Jie, et al.
Published: (2024)
by: Bian, Jie, et al.
Published: (2024)
Online Learning of Whittle Indices for Restless Bandits with Non-Stationary Transition Kernels
by: Shisher, Md Kamran Chowdhury, et al.
Published: (2025)
by: Shisher, Md Kamran Chowdhury, et al.
Published: (2025)
On Instability of Minimax Optimal Optimism-Based Bandit Algorithms
by: Praharaj, Samya, et al.
Published: (2025)
by: Praharaj, Samya, et al.
Published: (2025)
Evolution of Information in Interactive Decision Making: A Case Study for Multi-Armed Bandits
by: Gu, Yuzhou, et al.
Published: (2025)
by: Gu, Yuzhou, et al.
Published: (2025)
Asymptotically and Minimax Optimal Regret Bounds for Multi-Armed Bandits with Abstention
by: Yang, Junwen, et al.
Published: (2024)
by: Yang, Junwen, et al.
Published: (2024)
Improved Offline Contextual Bandits with Second-Order Bounds: Betting and Freezing
by: Ryu, J. Jon, et al.
Published: (2025)
by: Ryu, J. Jon, et al.
Published: (2025)
Statistical Complexity and Optimal Algorithms for Non-linear Ridge Bandits
by: Rajaraman, Nived, et al.
Published: (2023)
by: Rajaraman, Nived, et al.
Published: (2023)
ContextWIN: Whittle Index Based Mixture-of-Experts Neural Model For Restless Bandits Via Deep RL
by: Guo, Zhanqiu, et al.
Published: (2024)
by: Guo, Zhanqiu, et al.
Published: (2024)
Adaptive Smooth Non-Stationary Bandits
by: Suk, Joe
Published: (2024)
by: Suk, Joe
Published: (2024)
Avoiding the Price of Adaptivity: Inference in Linear Contextual Bandits via Stability
by: Praharaj, Samya, et al.
Published: (2025)
by: Praharaj, Samya, et al.
Published: (2025)
Concentrated Differential Privacy for Bandits
by: Azize, Achraf, et al.
Published: (2023)
by: Azize, Achraf, et al.
Published: (2023)
A Fast Binary Splitting Approach for Non-Adaptive Learning of Erdős--Rényi Graphs
by: Ta, Hoang, et al.
Published: (2025)
by: Ta, Hoang, et al.
Published: (2025)
Beam-aware Kernelized Contextual Bandits for User Association and Beamforming in mmWave Vehicular Networks
by: He, Xiaoyang, et al.
Published: (2026)
by: He, Xiaoyang, et al.
Published: (2026)
Similar Items
-
Diminishing Exploration: A Minimalist Approach to Piecewise Stationary Multi-Armed Bandits
by: Li, Kuan-Ta, et al.
Published: (2024) -
Non-Stationary Restless Multi-Armed Bandits with Provable Guarantee
by: Hung, Yu-Heng, et al.
Published: (2025) -
Restless Linear Bandits
by: Khaleghi, Azadeh
Published: (2024) -
Almost Minimax Optimal Best Arm Identification in Piecewise Stationary Linear Bandits
by: Hou, Yunlong, et al.
Published: (2024) -
Optimal Best Arm Identification with Fixed Confidence in Restless Bandits
by: Karthik, P. N., et al.
Published: (2023)