Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Botao, Honda, Junya |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Revisiting Follow-the-Perturbed-Leader with Unbounded Perturbations in Bandit Problems
by: Lee, Jongyeong, et al.
Published: (2025)
by: Lee, Jongyeong, et al.
Published: (2025)
A Further Efficient Algorithm with Best-of-Both-Worlds Guarantees for $m$-Set Semi-Bandit Problem
by: Chen, Botao, et al.
Published: (2026)
by: Chen, Botao, et al.
Published: (2026)
Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds
by: Lee, Jongyeong, et al.
Published: (2024)
by: Lee, Jongyeong, et al.
Published: (2024)
Follow-the-Perturbed-Leader Approaches Best-of-Both-Worlds for the m-Set Semi-Bandit Problems
by: Zhan, Jingxin, et al.
Published: (2025)
by: Zhan, Jingxin, et al.
Published: (2025)
The Survival Bandit Problem
by: Riou, Charles, et al.
Published: (2022)
by: Riou, Charles, et al.
Published: (2022)
Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds
by: Ito, Shinji, et al.
Published: (2024)
by: Ito, Shinji, et al.
Published: (2024)
Multi-Play Combinatorial Semi-Bandit Problem
by: Nakamura, Shintaro, et al.
Published: (2025)
by: Nakamura, Shintaro, et al.
Published: (2025)
Multi-Player Approaches for Dueling Bandits
by: Raveh, Or, et al.
Published: (2024)
by: Raveh, Or, et al.
Published: (2024)
Follow-the-Perturbed-Leader for Decoupled Bandits: Best-of-Both-Worlds and Practicality
by: Kim, Chaiwon, et al.
Published: (2025)
by: Kim, Chaiwon, et al.
Published: (2025)
A General Recipe for the Analysis of Randomized Multi-Armed Bandit Algorithms
by: Baudry, Dorian, et al.
Published: (2023)
by: Baudry, Dorian, et al.
Published: (2023)
Oracle-Efficient Combinatorial Semi-Bandits
by: Kim, Jung-hun, et al.
Published: (2025)
by: Kim, Jung-hun, et al.
Published: (2025)
Merit-based Fair Combinatorial Semi-Bandit with Unrestricted Feedback Delays
by: Chen, Ziqun, et al.
Published: (2024)
by: Chen, Ziqun, et al.
Published: (2024)
Combinatorial Rising Bandits
by: Song, Seockbean, et al.
Published: (2024)
by: Song, Seockbean, et al.
Published: (2024)
Efficient Best-of-Both-Worlds Algorithms for Contextual Combinatorial Semi-Bandits
by: Li, Mengmeng, et al.
Published: (2025)
by: Li, Mengmeng, et al.
Published: (2025)
Worst-Case Regret Bounds for Combinatorial Thompson Sampling in Sleeping Semi-Bandits
by: Huang, Zhiming, et al.
Published: (2026)
by: Huang, Zhiming, et al.
Published: (2026)
Near-Optimal Regret for Efficient Stochastic Combinatorial Semi-Bandits
by: Ye, Zichun, et al.
Published: (2025)
by: Ye, Zichun, et al.
Published: (2025)
Combinatorial Logistic Bandits
by: Liu, Xutong, et al.
Published: (2024)
by: Liu, Xutong, et al.
Published: (2024)
Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits
by: Zhou, Julien, et al.
Published: (2024)
by: Zhou, Julien, et al.
Published: (2024)
From Contextual Combinatorial Semi-Bandits to Bandit List Classification: Improved Sample Complexity with Sparse Rewards
by: Erez, Liad, et al.
Published: (2025)
by: Erez, Liad, et al.
Published: (2025)
Combinatorial Bandit Bayesian Optimization for Tensor Outputs
by: Huang, Jingru, et al.
Published: (2026)
by: Huang, Jingru, et al.
Published: (2026)
Offline Learning for Combinatorial Multi-armed Bandits
by: Liu, Xutong, et al.
Published: (2025)
by: Liu, Xutong, et al.
Published: (2025)
Rate-optimal Design for Anytime Best Arm Identification
by: Komiyama, Junpei, et al.
Published: (2025)
by: Komiyama, Junpei, et al.
Published: (2025)
Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring
by: Tsuchiya, Taira, et al.
Published: (2024)
by: Tsuchiya, Taira, et al.
Published: (2024)
Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds
by: Tsuchiya, Taira, et al.
Published: (2023)
by: Tsuchiya, Taira, et al.
Published: (2023)
Thompson Exploration with Best Challenger Rule in Best Arm Identification
by: Lee, Jongyeong, et al.
Published: (2023)
by: Lee, Jongyeong, et al.
Published: (2023)
Optimal Regret of Bernoulli Bandits under Global Differential Privacy
by: Azize, Achraf, et al.
Published: (2025)
by: Azize, Achraf, et al.
Published: (2025)
Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms
by: Liu, Xutong, et al.
Published: (2022)
by: Liu, Xutong, et al.
Published: (2022)
Adversarial Combinatorial Bandits with Switching Costs
by: Dong, Yanyan, et al.
Published: (2024)
by: Dong, Yanyan, et al.
Published: (2024)
Combinatorial Causal Bandits without Graph Skeleton
by: Feng, Shi, et al.
Published: (2023)
by: Feng, Shi, et al.
Published: (2023)
Leader Reward for POMO-Based Neural Combinatorial Optimization
by: Wang, Chaoyang, et al.
Published: (2024)
by: Wang, Chaoyang, et al.
Published: (2024)
Hybrid Combinatorial Multi-armed Bandits with Probabilistically Triggered Arms
by: Zhou, Kongchang, et al.
Published: (2025)
by: Zhou, Kongchang, et al.
Published: (2025)
On the Regularity and Fairness of Combinatorial Multi-Armed Bandit
by: Wu, Xiaoyi, et al.
Published: (2025)
by: Wu, Xiaoyi, et al.
Published: (2025)
Combinatorial Allocation Bandits with Nonlinear Arm Utility
by: Shibukawa, Yuki, et al.
Published: (2026)
by: Shibukawa, Yuki, et al.
Published: (2026)
Efficient Swap Regret Minimization in Combinatorial Bandits
by: Kontogiannis, Andreas, et al.
Published: (2026)
by: Kontogiannis, Andreas, et al.
Published: (2026)
Multi-Task Combinatorial Bandits for Budget Allocation
by: Ge, Lin, et al.
Published: (2024)
by: Ge, Lin, et al.
Published: (2024)
Multi-Agent Combinatorial-Multi-Armed-Bandit framework for the Submodular Welfare Problem under Bandit Feedback
by: Pokhriyal, Subham, et al.
Published: (2026)
by: Pokhriyal, Subham, et al.
Published: (2026)
Contextual Combinatorial Bandits with Probabilistically Triggered Arms
by: Liu, Xutong, et al.
Published: (2023)
by: Liu, Xutong, et al.
Published: (2023)
Self-Concordant Perturbations for Linear Bandits
by: Lévy, Lucas, et al.
Published: (2025)
by: Lévy, Lucas, et al.
Published: (2025)
Learning with Posterior Sampling for Revenue Management under Time-varying Demand
by: Shimizu, Kazuma, et al.
Published: (2024)
by: Shimizu, Kazuma, et al.
Published: (2024)
Optimal Arm Elimination Algorithms for Combinatorial Bandits
by: Wen, Yuxiao, et al.
Published: (2025)
by: Wen, Yuxiao, et al.
Published: (2025)
Similar Items
-
Revisiting Follow-the-Perturbed-Leader with Unbounded Perturbations in Bandit Problems
by: Lee, Jongyeong, et al.
Published: (2025) -
A Further Efficient Algorithm with Best-of-Both-Worlds Guarantees for $m$-Set Semi-Bandit Problem
by: Chen, Botao, et al.
Published: (2026) -
Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds
by: Lee, Jongyeong, et al.
Published: (2024) -
Follow-the-Perturbed-Leader Approaches Best-of-Both-Worlds for the m-Set Semi-Bandit Problems
by: Zhan, Jingxin, et al.
Published: (2025) -
The Survival Bandit Problem
by: Riou, Charles, et al.
Published: (2022)