Saved in:
| Main Authors: | Lim, Eugene, Tan, Vincent Y. F., Soh, Harold |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.05856 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
p-Mean Regret for Stochastic Bandits
by: Krishna, Anand, et al.
Published: (2024)
by: Krishna, Anand, et al.
Published: (2024)
Adversarial Combinatorial Bandits with Switching Costs
by: Dong, Yanyan, et al.
Published: (2024)
by: Dong, Yanyan, et al.
Published: (2024)
Don't Start from Scratch: Behavioral Refinement via Interpolant-based Policy Diffusion
by: Chen, Kaiqi, et al.
Published: (2024)
by: Chen, Kaiqi, et al.
Published: (2024)
Optimal Clustering with Bandit Feedback
by: Yang, Junwen, et al.
Published: (2022)
by: Yang, Junwen, et al.
Published: (2022)
Indexed Minimum Empirical Divergence-Based Algorithms for Linear Bandits
by: Bian, Jie, et al.
Published: (2024)
by: Bian, Jie, et al.
Published: (2024)
Bandit Convex Optimization with Gradient Prediction Adaptivity
by: Wang, Shuche, et al.
Published: (2026)
by: Wang, Shuche, et al.
Published: (2026)
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)
Quantum-Enhanced Neural Contextual Bandit Algorithms
by: Huang, Yuqi, et al.
Published: (2026)
by: Huang, Yuqi, et al.
Published: (2026)
On the Benefits of Free Exploration for Regret Minimization in Multi-Armed Bandits
by: Hou, Yunlong, et al.
Published: (2026)
by: Hou, Yunlong, et al.
Published: (2026)
Influence Maximization via Graph Neural Bandits
by: Feng, Yuting, et al.
Published: (2024)
by: Feng, Yuting, et al.
Published: (2024)
Know When to Abstain: Optimal Selective Classification with Likelihood Ratios
by: Heng, Alvin, et al.
Published: (2025)
by: Heng, Alvin, et al.
Published: (2025)
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)
Imitation Learning with Limited Actions via Diffusion Planners and Deep Koopman Controllers
by: Bi, Jianxin, et al.
Published: (2024)
by: Bi, Jianxin, et al.
Published: (2024)
On the Convergence of (Stochastic) Gradient Descent for Kolmogorov--Arnold Networks
by: Gao, Yihang, et al.
Published: (2024)
by: Gao, Yihang, et al.
Published: (2024)
Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Construction
by: Zhang, Bowen, et al.
Published: (2024)
by: Zhang, Bowen, et al.
Published: (2024)
BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms
by: Hou, Yunlong, et al.
Published: (2025)
by: Hou, Yunlong, et al.
Published: (2025)
Action Hallucination in Generative Vision-Language-Action Models
by: Soh, Harold, et al.
Published: (2026)
by: Soh, Harold, et al.
Published: (2026)
Large Language Models as Zero-Shot Human Models for Human-Robot Interaction
by: Zhang, Bowen, et al.
Published: (2023)
by: Zhang, Bowen, et al.
Published: (2023)
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)
Parameter-free Algorithms for the Stochastically Extended Adversarial Model
by: Wang, Shuche, et al.
Published: (2025)
by: Wang, Shuche, et al.
Published: (2025)
Challenges in Credit Assignment for Multi-Agent Reinforcement Learning in Open Agent Systems
by: Abadi, Alireza Saleh, et al.
Published: (2025)
by: Abadi, Alireza Saleh, et al.
Published: (2025)
Stochastic Gradient Succeeds for Bandits
by: Mei, Jincheng, et al.
Published: (2024)
by: Mei, Jincheng, et al.
Published: (2024)
Efficient Clustering in Stochastic Bandits
by: Chandran, G Dhinesh, et al.
Published: (2026)
by: Chandran, G Dhinesh, et al.
Published: (2026)
Out-of-Distribution Detection with a Single Unconditional Diffusion Model
by: Heng, Alvin, et al.
Published: (2024)
by: Heng, Alvin, et al.
Published: (2024)
Generative Modeling with Flow-Guided Density Ratio Learning
by: Heng, Alvin, et al.
Published: (2023)
by: Heng, Alvin, et al.
Published: (2023)
Bayesian Bandit Algorithms with Approximate Inference in Stochastic Linear Bandits
by: Huang, Ziyi, et al.
Published: (2024)
by: Huang, Ziyi, et al.
Published: (2024)
Stochastic Clock Attention for Aligning Continuous and Ordered Sequences
by: Soh, Hyungjoon, et al.
Published: (2025)
by: Soh, Hyungjoon, et al.
Published: (2025)
Egalitarian Gradient Descent: A Simple Approach to Accelerated Grokking
by: Pasand, Ali Saheb, et al.
Published: (2025)
by: Pasand, Ali Saheb, et al.
Published: (2025)
LTLDoG: Satisfying Temporally-Extended Symbolic Constraints for Safe Diffusion-based Planning
by: Feng, Zeyu, et al.
Published: (2024)
by: Feng, Zeyu, et al.
Published: (2024)
Are Stochastic Multi-objective Bandits Harder than Single-objective Bandits?
by: Guan, Changkun, et al.
Published: (2026)
by: Guan, Changkun, et al.
Published: (2026)
Batched Stochastic Bandit for Nondegenerate Functions
by: Liu, Yu, et al.
Published: (2024)
by: Liu, Yu, et al.
Published: (2024)
Stochastic Bandits Robust to Adversarial Attacks
by: Wang, Xuchuang, et al.
Published: (2024)
by: Wang, Xuchuang, et al.
Published: (2024)
Lipschitz Bandits with Stochastic Delayed Feedback
by: Liu, Zhongxuan, et al.
Published: (2025)
by: Liu, Zhongxuan, et al.
Published: (2025)
Stochastic $k$-Submodular Bandits with Full Bandit Feedback
by: Nie, Guanyu, et al.
Published: (2024)
by: Nie, Guanyu, et al.
Published: (2024)
Biased Dueling Bandits with Stochastic Delayed Feedback
by: Yi, Bongsoo, et al.
Published: (2024)
by: Yi, Bongsoo, et al.
Published: (2024)
Stochastic Graph Bandit Learning with Side-Observations
by: Gong, Xueping, et al.
Published: (2023)
by: Gong, Xueping, et al.
Published: (2023)
Stochastic Matching Bandits with Rare Optimization Updates
by: Kim, Jung-hun, et al.
Published: (2025)
by: Kim, Jung-hun, et al.
Published: (2025)
Conformal-Style Quantile Analyses for Stochastic Bandits
by: Du, Chengyu, et al.
Published: (2026)
by: Du, Chengyu, et al.
Published: (2026)
Active Learning for Stochastic Contextual Linear Bandits
by: Brunskill, Emma, et al.
Published: (2026)
by: Brunskill, Emma, et al.
Published: (2026)
Similar Items
-
p-Mean Regret for Stochastic Bandits
by: Krishna, Anand, et al.
Published: (2024) -
Adversarial Combinatorial Bandits with Switching Costs
by: Dong, Yanyan, et al.
Published: (2024) -
Don't Start from Scratch: Behavioral Refinement via Interpolant-based Policy Diffusion
by: Chen, Kaiqi, et al.
Published: (2024) -
Optimal Clustering with Bandit Feedback
by: Yang, Junwen, et al.
Published: (2022) -
Indexed Minimum Empirical Divergence-Based Algorithms for Linear Bandits
by: Bian, Jie, et al.
Published: (2024)