Contextual Combinatorial Bandits with Probabilistically Triggered Arms
Fuente:
arXiv
Saved in:
| Main Authors: | Liu, Xutong, Zuo, Jinhang, Wang, Siwei, Lui, John C. S., Hajiesmaili, Mohammad, Wierman, Adam, Chen, Wei |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
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)
Fusing Reward and Dueling Feedback in Stochastic Bandits
by: Wang, Xuchuang, et al.
Published: (2025)
by: Wang, Xuchuang, et al.
Published: (2025)
Stochastic Bandits Robust to Adversarial Attacks
by: Wang, Xuchuang, et al.
Published: (2024)
by: Wang, Xuchuang, et al.
Published: (2024)
Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond
by: Liu, Xutong, et al.
Published: (2024)
by: Liu, Xutong, et al.
Published: (2024)
Combinatorial Logistic Bandits
by: Liu, Xutong, et al.
Published: (2024)
by: Liu, Xutong, et al.
Published: (2024)
Offline Learning for Combinatorial Multi-armed Bandits
by: Liu, Xutong, et al.
Published: (2025)
by: Liu, Xutong, et al.
Published: (2025)
Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users
by: Yang, Hantao, et al.
Published: (2024)
by: Yang, Hantao, et al.
Published: (2024)
Heterogeneous Multi-Agent Bandits with Parsimonious Hints
by: Mirfakhar, Amirmahdi, et al.
Published: (2025)
by: Mirfakhar, Amirmahdi, et al.
Published: (2025)
Online Multi-LLM Selection via Contextual Bandits under Unstructured Context Evolution
by: Poon, Manhin, et al.
Published: (2025)
by: Poon, Manhin, et al.
Published: (2025)
Hybrid Combinatorial Multi-armed Bandits with Probabilistically Triggered Arms
by: Zhou, Kongchang, et al.
Published: (2025)
by: Zhou, Kongchang, et al.
Published: (2025)
Towards Environmentally Equitable AI
by: Hajiesmaili, Mohammad, et al.
Published: (2024)
by: Hajiesmaili, Mohammad, et al.
Published: (2024)
Leveraging the Power of Conversations: Optimal Key Term Selection in Conversational Contextual Bandits
by: Liu, Maoli, et al.
Published: (2025)
by: Liu, Maoli, et al.
Published: (2025)
Multi-Agent Stochastic Bandits Robust to Adversarial Corruptions
by: Ghaffari, Fatemeh, et al.
Published: (2024)
by: Ghaffari, Fatemeh, et al.
Published: (2024)
A Contextual Combinatorial Bandit Approach to Negotiation
by: Li, Yexin, et al.
Published: (2024)
by: Li, Yexin, et al.
Published: (2024)
Effective Off-Policy Evaluation and Learning in Contextual Combinatorial Bandits
by: Shimizu, Tatsuhiro, et al.
Published: (2024)
by: Shimizu, Tatsuhiro, et al.
Published: (2024)
KL-regularization Itself is Differentially Private in Bandits and RLHF
by: Zhang, Yizhou, et al.
Published: (2025)
by: Zhang, Yizhou, et al.
Published: (2025)
FedConPE: Efficient Federated Conversational Bandits with Heterogeneous Clients
by: Li, Zhuohua, et al.
Published: (2024)
by: Li, Zhuohua, 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)
Steering Frozen LLMs: Adaptive Social Alignment via Online Prompt Routing
by: Zhang, Zeyu, et al.
Published: (2026)
by: Zhang, Zeyu, et al.
Published: (2026)
Offline Clustering of Linear Bandits: The Power of Clusters under Limited Data
by: Liu, Jingyuan, et al.
Published: (2025)
by: Liu, Jingyuan, et al.
Published: (2025)
Practical Adversarial Attacks on Stochastic Bandits via Fake Data Injection
by: Zeng, Qirun, et al.
Published: (2025)
by: Zeng, Qirun, et al.
Published: (2025)
A Unified Online-Offline Framework for Co-Branding Campaign Recommendations
by: Dai, Xiangxiang, et al.
Published: (2025)
by: Dai, Xiangxiang, et al.
Published: (2025)
Conservative Contextual Bandits: Beyond Linear Representations
by: Deb, Rohan, et al.
Published: (2024)
by: Deb, Rohan, et al.
Published: (2024)
Demystifying Online Clustering of Bandits: Enhanced Exploration Under Stochastic and Smoothed Adversarial Contexts
by: Li, Zhuohua, et al.
Published: (2025)
by: Li, Zhuohua, et al.
Published: (2025)
HiLoRA: Adaptive Hierarchical LoRA Routing for Training-Free Domain Generalization
by: Han, Ziyi, et al.
Published: (2025)
by: Han, Ziyi, et al.
Published: (2025)
Variance-Dependent Regret Bounds for Non-stationary Linear Bandits
by: Wang, Zhiyong, et al.
Published: (2024)
by: Wang, Zhiyong, et al.
Published: (2024)
On-line Learning in Tree MDPs by Treating Policies as Bandit Arms
by: Shah, Anvay, et al.
Published: (2026)
by: Shah, Anvay, et al.
Published: (2026)
Semantic Caching for Low-Cost LLM Serving: From Offline Learning to Online Adaptation
by: Liu, Xutong, et al.
Published: (2025)
by: Liu, Xutong, et al.
Published: (2025)
Cost-Effective Online Multi-LLM Selection with Versatile Reward Models
by: Dai, Xiangxiang, et al.
Published: (2024)
by: Dai, Xiangxiang, et al.
Published: (2024)
Online Clustering of Dueling Bandits
by: Wang, Zhiyong, et al.
Published: (2025)
by: Wang, Zhiyong, et al.
Published: (2025)
Best Arm Identification in Generalized Linear Bandits via Hybrid Feedback
by: Zeng, Qirun, et al.
Published: (2026)
by: Zeng, Qirun, et al.
Published: (2026)
Large Language Model-Enhanced Multi-Armed Bandits
by: Sun, Jiahang, et al.
Published: (2025)
by: Sun, Jiahang, et al.
Published: (2025)
Tree Ensembles for Contextual Bandits
by: Nilsson, Hannes, et al.
Published: (2024)
by: Nilsson, Hannes, et al.
Published: (2024)
Online Learning to Rank under Corruption: A Robust Cascading Bandits Approach
by: Ghaffari, Fatemeh, et al.
Published: (2025)
by: Ghaffari, Fatemeh, et al.
Published: (2025)
Contextual Rollout Bandits for Reinforcement Learning with Verifiable Rewards
by: Lu, Xiaodong, et al.
Published: (2026)
by: Lu, Xiaodong, et al.
Published: (2026)
Bayesian Analysis of Combinatorial Gaussian Process Bandits
by: Sandberg, Jack, et al.
Published: (2023)
by: Sandberg, Jack, et al.
Published: (2023)
The Sample Complexity of Multiclass and Sparse Contextual Bandits
by: Erez, Liad, et al.
Published: (2026)
by: Erez, Liad, et al.
Published: (2026)
Neural Combinatorial Clustered Bandits for Recommendation Systems
by: Atalar, Baran, et al.
Published: (2024)
by: Atalar, Baran, et al.
Published: (2024)
Causal Contextual Bandits with Adaptive Context
by: Madhavan, Rahul, et al.
Published: (2024)
by: Madhavan, Rahul, et al.
Published: (2024)
Diffusion Models Meet Contextual Bandits
by: Aouali, Imad
Published: (2024)
by: Aouali, Imad
Published: (2024)
Similar Items
-
Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms
by: Liu, Xutong, et al.
Published: (2022) -
Fusing Reward and Dueling Feedback in Stochastic Bandits
by: Wang, Xuchuang, et al.
Published: (2025) -
Stochastic Bandits Robust to Adversarial Attacks
by: Wang, Xuchuang, et al.
Published: (2024) -
Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond
by: Liu, Xutong, et al.
Published: (2024) -
Combinatorial Logistic Bandits
by: Liu, Xutong, et al.
Published: (2024)