Neural Variance-aware Dueling Bandits with Deep Representation and Shallow Exploration
Fuente:
arXiv
Saved in:
| Main Authors: | Oh, Youngmin, Park, Jinje, Paik, Taejin, Park, Jaemin |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
M3: Mamba-assisted Multi-Circuit Optimization via MBRL with Effective Scheduling
by: Oh, Youngmin, et al.
Published: (2024)
by: Oh, Youngmin, et al.
Published: (2024)
Robust Linear Dueling Bandits with Post-serving Context under Unknown Delays and Adversarial Corruptions
by: Oh, Youngmin
Published: (2026)
by: Oh, Youngmin
Published: (2026)
Variance-Aware Regret Bounds for Stochastic Contextual Dueling Bandits
by: Di, Qiwei, et al.
Published: (2023)
by: Di, Qiwei, et al.
Published: (2023)
Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits
by: Bui, Ha Manh, et al.
Published: (2024)
by: Bui, Ha Manh, et al.
Published: (2024)
Linear and Neural Dueling Bandits with Delayed Feedback
by: Wang, Xiangyi, et al.
Published: (2026)
by: Wang, Xiangyi, et al.
Published: (2026)
Federated Linear Dueling Bandits
by: Huang, Xuhan, et al.
Published: (2025)
by: Huang, Xuhan, et al.
Published: (2025)
Online Clustering of Dueling Bandits
by: Wang, Zhiyong, et al.
Published: (2025)
by: Wang, Zhiyong, et al.
Published: (2025)
Multi-Player Approaches for Dueling Bandits
by: Raveh, Or, et al.
Published: (2024)
by: Raveh, Or, et al.
Published: (2024)
PIG: Physics-Informed Gaussians as Adaptive Parametric Mesh Representations
by: Kang, Namgyu, et al.
Published: (2024)
by: Kang, Namgyu, et al.
Published: (2024)
Active Human Feedback Collection via Neural Contextual Dueling Bandits
by: Verma, Arun, et al.
Published: (2025)
by: Verma, Arun, et al.
Published: (2025)
Neural Dueling Bandits: Preference-Based Optimization with Human Feedback
by: Verma, Arun, et al.
Published: (2024)
by: Verma, Arun, 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)
The Sampling Complexity of Condorcet Winner Identification in Dueling Bandits
by: Saad, El Mehdi, et al.
Published: (2026)
by: Saad, El Mehdi, et al.
Published: (2026)
Fusing Reward and Dueling Feedback in Stochastic Bandits
by: Wang, Xuchuang, et al.
Published: (2025)
by: Wang, Xuchuang, et al.
Published: (2025)
Conversational Dueling Bandits in Generalized Linear Models
by: Yang, Shuhua, et al.
Published: (2024)
by: Yang, Shuhua, et al.
Published: (2024)
Infrequent Exploration in Linear Bandits
by: Lee, Harin, et al.
Published: (2025)
by: Lee, Harin, et al.
Published: (2025)
Recycling History: Efficient Recommendations from Contextual Dueling Bandits
by: Sankagiri, Suryanarayana, et al.
Published: (2025)
by: Sankagiri, Suryanarayana, et al.
Published: (2025)
Utility-based Dueling Bandits as a Partial Monitoring Game
by: Gajane, Pratik, et al.
Published: (2015)
by: Gajane, Pratik, et al.
Published: (2015)
Feel-Good Thompson Sampling for Contextual Dueling Bandits
by: Li, Xuheng, et al.
Published: (2024)
by: Li, Xuheng, et al.
Published: (2024)
PINT: Physics-Informed Neural Time Series Models with Applications to Long-term Inference on WeatherBench 2m-Temperature Data
by: Park, Keonvin, et al.
Published: (2025)
by: Park, Keonvin, et al.
Published: (2025)
When Can We Track Significant Preference Shifts in Dueling Bandits?
by: Suk, Joe, et al.
Published: (2023)
by: Suk, Joe, et al.
Published: (2023)
Nearly Optimal Algorithms for Contextual Dueling Bandits from Adversarial Feedback
by: Di, Qiwei, et al.
Published: (2024)
by: Di, Qiwei, et al.
Published: (2024)
Non-Stationary Dueling Bandits Under a Weighted Borda Criterion
by: Suk, Joe, et al.
Published: (2024)
by: Suk, Joe, et al.
Published: (2024)
FlexiQ: Adaptive Mixed-Precision Quantization for Latency/Accuracy Trade-Offs in Deep Neural Networks
by: Kim, Jaemin, et al.
Published: (2025)
by: Kim, Jaemin, et al.
Published: (2025)
Thompson Sampling for Multi-Objective Linear Contextual Bandit
by: Park, Somangchan, et al.
Published: (2025)
by: Park, Somangchan, et al.
Published: (2025)
Exploration via Feature Perturbation in Contextual Bandits
by: Yi, Seouh-won, et al.
Published: (2025)
by: Yi, Seouh-won, et al.
Published: (2025)
Lipschitz Dueling Bandits over Continuous Action Spaces
by: Sharma, Mudit, et al.
Published: (2026)
by: Sharma, Mudit, et al.
Published: (2026)
Preference is More Than Comparisons: Rethinking Dueling Bandits with Augmented Human Feedback
by: Wang, Shengbo, et al.
Published: (2025)
by: Wang, Shengbo, et al.
Published: (2025)
Neural Exploitation and Exploration of Contextual Bandits
by: Ban, Yikun, et al.
Published: (2023)
by: Ban, Yikun, et al.
Published: (2023)
Beyond Numeric Rewards: In-Context Dueling Bandits with LLM Agents
by: Xia, Fanzeng, et al.
Published: (2024)
by: Xia, Fanzeng, et al.
Published: (2024)
Multi-User Dueling Bandits: A Fair Approach using Nash Social Welfare
by: Ahmed, Maheed H., et al.
Published: (2026)
by: Ahmed, Maheed H., et al.
Published: (2026)
Linear Bandits with Partially Observable Features
by: Kim, Wonyoung, et al.
Published: (2025)
by: Kim, Wonyoung, et al.
Published: (2025)
Reparameterizing 4DVAR with neural fields
by: Oh, Jaemin
Published: (2025)
by: Oh, Jaemin
Published: (2025)
Dueling Deep Reinforcement Learning for Financial Time Series
by: Giorgio, Bruno
Published: (2025)
by: Giorgio, Bruno
Published: (2025)
Posterior Inference on Shallow Infinitely Wide Bayesian Neural Networks under Weights with Unbounded Variance
by: Loría, Jorge, et al.
Published: (2023)
by: Loría, Jorge, et al.
Published: (2023)
Global Context-aware Representation Learning for Spatially Resolved Transcriptomics
by: Oh, Yunhak, et al.
Published: (2025)
by: Oh, Yunhak, et al.
Published: (2025)
Coupling-Robust Accuracy in Multiphysics Physics Informed Neural Networks via Kronecker-Preconditioned Optimization
by: Park, Youngjae, et al.
Published: (2026)
by: Park, Youngjae, et al.
Published: (2026)
On Transportability for Structural Causal Bandits
by: Park, Min Woo, et al.
Published: (2025)
by: Park, Min Woo, et al.
Published: (2025)
Understanding NTK Variance in Implicit Neural Representations
by: Ou, Chengguang, et al.
Published: (2025)
by: Ou, Chengguang, et al.
Published: (2025)
Separable Physics-informed Neural Networks for Solving the BGK Model of the Boltzmann Equation
by: Oh, Jaemin, et al.
Published: (2024)
by: Oh, Jaemin, et al.
Published: (2024)
Similar Items
-
M3: Mamba-assisted Multi-Circuit Optimization via MBRL with Effective Scheduling
by: Oh, Youngmin, et al.
Published: (2024) -
Robust Linear Dueling Bandits with Post-serving Context under Unknown Delays and Adversarial Corruptions
by: Oh, Youngmin
Published: (2026) -
Variance-Aware Regret Bounds for Stochastic Contextual Dueling Bandits
by: Di, Qiwei, et al.
Published: (2023) -
Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits
by: Bui, Ha Manh, et al.
Published: (2024) -
Linear and Neural Dueling Bandits with Delayed Feedback
by: Wang, Xiangyi, et al.
Published: (2026)