A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
Fuente:
arXiv
Saved in:
| Main Authors: | Lee, Junghyun, Yun, Se-Young, Jun, Kwang-Sung |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion
by: Lee, Junghyun, et al.
Published: (2023)
by: Lee, Junghyun, et al.
Published: (2023)
A Jointly Efficient and Optimal Algorithm for Heteroskedastic Generalized Linear Bandits with Adversarial Corruptions
by: Kim, Sanghwa, et al.
Published: (2026)
by: Kim, Sanghwa, et al.
Published: (2026)
Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization
by: Jun, Kwang-Sung, et al.
Published: (2024)
by: Jun, Kwang-Sung, et al.
Published: (2024)
GL-LowPopArt: A Nearly Instance-Wise Minimax-Optimal Estimator for Generalized Low-Rank Trace Regression
by: Lee, Junghyun, et al.
Published: (2025)
by: Lee, Junghyun, et al.
Published: (2025)
Regularized Online RLHF with Generalized Bilinear Preferences
by: Lee, Junghyun, et al.
Published: (2026)
by: Lee, Junghyun, et al.
Published: (2026)
Flooding with Absorption: An Efficient Protocol for Heterogeneous Bandits over Complex Networks
by: Lee, Junghyun, et al.
Published: (2023)
by: Lee, Junghyun, et al.
Published: (2023)
Minimum Empirical Divergence for Sub-Gaussian Linear Bandits
by: Balagopalan, Kapilan, et al.
Published: (2024)
by: Balagopalan, Kapilan, et al.
Published: (2024)
Probability-Flow ODE in Infinite-Dimensional Function Spaces
by: Na, Kunwoo, et al.
Published: (2025)
by: Na, Kunwoo, et al.
Published: (2025)
Adversarial Bandits against Arbitrary Strategies
by: Kim, Jung-hun, et al.
Published: (2022)
by: Kim, Jung-hun, et al.
Published: (2022)
An Adaptive Approach for Infinitely Many-armed Bandits under Generalized Rotting Constraints
by: Kim, Jung-hun, et al.
Published: (2024)
by: Kim, Jung-hun, et al.
Published: (2024)
Near-Optimal Clustering in Mixture of Markov Chains
by: Lee, Junghyun, et al.
Published: (2025)
by: Lee, Junghyun, et al.
Published: (2025)
Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles
by: Kim, Jung-hun, et al.
Published: (2017)
by: Kim, Jung-hun, et al.
Published: (2017)
Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards
by: Qin, Hao, et al.
Published: (2023)
by: Qin, Hao, et al.
Published: (2023)
Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits
by: Jang, Kyoungseok, et al.
Published: (2024)
by: Jang, Kyoungseok, et al.
Published: (2024)
Instance-Optimal Estimation with Multiple LLM Judges on a Budget
by: Lee, Junghyun, et al.
Published: (2026)
by: Lee, Junghyun, et al.
Published: (2026)
MEC: Machine-Learning-Assisted Generalized Entropy Calibration for Semi-Supervised Mean Estimation
by: Lee, Se Yoon, et al.
Published: (2026)
by: Lee, Se Yoon, et al.
Published: (2026)
Nearly Optimal Active Preference Learning and Its Application to LLM Alignment
by: Zhao, Yao, et al.
Published: (2026)
by: Zhao, Yao, et al.
Published: (2026)
Confidence Sequences for Generalized Linear Models via Regret Analysis
by: Clerico, Eugenio, et al.
Published: (2025)
by: Clerico, Eugenio, et al.
Published: (2025)
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)
Beyond RLHF: A Unified Theoretical Framework of Alignment
by: Yun, Jihun, et al.
Published: (2025)
by: Yun, Jihun, et al.
Published: (2025)
Coverage Improvement and Fast Convergence of On-policy Preference Learning
by: Kim, Juno, et al.
Published: (2026)
by: Kim, Juno, et al.
Published: (2026)
Improved Online Confidence Bounds for Multinomial Logistic Bandits
by: Lee, Joongkyu, et al.
Published: (2025)
by: Lee, Joongkyu, et al.
Published: (2025)
FlickerFusion: Intra-trajectory Domain Generalizing Multi-Agent RL
by: Koh, Woosung, et al.
Published: (2024)
by: Koh, Woosung, et al.
Published: (2024)
LinearAPT: An Adaptive Algorithm for the Fixed-Budget Thresholding Linear Bandit Problem
by: Wu, Yun-Ang, et al.
Published: (2024)
by: Wu, Yun-Ang, et al.
Published: (2024)
Nonstationary Generalized Linear Bandits with Discounted Online Mirror Descent
by: Lee, Joongkyu, et al.
Published: (2026)
by: Lee, Joongkyu, et al.
Published: (2026)
Infrequent Exploration in Linear Bandits
by: Lee, Harin, et al.
Published: (2025)
by: Lee, Harin, et al.
Published: (2025)
Second-Order Bounds for [0,1]-Valued Regression via Betting Loss
by: Li, Yinan, et al.
Published: (2025)
by: Li, Yinan, et al.
Published: (2025)
HAVER: Instance-Dependent Error Bounds for Maximum Mean Estimation and Applications to Q-Learning and Monte Carlo Tree Search
by: Nguyen, Tuan Ngo, et al.
Published: (2024)
by: Nguyen, Tuan Ngo, et al.
Published: (2024)
Online Continuous Hyperparameter Optimization for Generalized Linear Contextual Bandits
by: Kang, Yue, et al.
Published: (2023)
by: Kang, Yue, et al.
Published: (2023)
Conversational Dueling Bandits in Generalized Linear Models
by: Yang, Shuhua, et al.
Published: (2024)
by: Yang, Shuhua, et al.
Published: (2024)
Generalized Linear Bandits with Limited Adaptivity
by: Sawarni, Ayush, et al.
Published: (2024)
by: Sawarni, Ayush, et al.
Published: (2024)
Hypernetwork-Driven Model Fusion for Federated Domain Generalization
by: Bartholet, Marc, et al.
Published: (2024)
by: Bartholet, Marc, et al.
Published: (2024)
What is the Alignment Objective of GRPO?
by: Vojnovic, Milan, et al.
Published: (2025)
by: Vojnovic, Milan, et al.
Published: (2025)
Generative Visual Code Mobile World Models
by: Koh, Woosung, et al.
Published: (2026)
by: Koh, Woosung, et al.
Published: (2026)
Single Index Bandits: Generalized Linear Contextual Bandits with Unknown Reward Functions
by: Kang, Yue, et al.
Published: (2025)
by: Kang, Yue, et al.
Published: (2025)
Robust Causal Bandits for Linear Models
by: Yan, Zirui, et al.
Published: (2023)
by: Yan, Zirui, et al.
Published: (2023)
Fixed Budget is No Harder Than Fixed Confidence in Best-Arm Identification up to Logarithmic Factors
by: Balagopalan, Kapilan, et al.
Published: (2026)
by: Balagopalan, Kapilan, et al.
Published: (2026)
Revisiting Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model
by: Ariu, Kaito, et al.
Published: (2023)
by: Ariu, Kaito, et al.
Published: (2023)
$\varepsilon$-Good Action Identification in Fixed-Budget Monte Carlo Tree Search
by: Li, Yinan, et al.
Published: (2026)
by: Li, Yinan, et al.
Published: (2026)
Ranking In Generalized Linear Bandits
by: Shidani, Amitis, et al.
Published: (2022)
by: Shidani, Amitis, et al.
Published: (2022)
Similar Items
-
Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion
by: Lee, Junghyun, et al.
Published: (2023) -
A Jointly Efficient and Optimal Algorithm for Heteroskedastic Generalized Linear Bandits with Adversarial Corruptions
by: Kim, Sanghwa, et al.
Published: (2026) -
Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization
by: Jun, Kwang-Sung, et al.
Published: (2024) -
GL-LowPopArt: A Nearly Instance-Wise Minimax-Optimal Estimator for Generalized Low-Rank Trace Regression
by: Lee, Junghyun, et al.
Published: (2025) -
Regularized Online RLHF with Generalized Bilinear Preferences
by: Lee, Junghyun, et al.
Published: (2026)