6 papers
Conditional Evaluation of Language Models with Cheap Auxiliary Signals
Zhi Zhang, Lingfeng Lyu, Yue Kang +1
Aggregate accuracy hides where models succeed and fail. Estimating conditional performance profiles from gold labels alone is expensive, while cheap auxiliary signals such as LLM-j…
Lipschitz Bandits with Stochastic Delayed Feedback
Zhongxuan Liu, Yue Kang, Thomas C. M. Lee
The Lipschitz bandit problem extends stochastic bandits to a continuous action set defined over a metric space, where the expected reward function satisfies a Lipschitz condition.…
Generalized Low-Rank Matrix Contextual Bandits with Graph Information
Yao Wang, Jiannan Li, Yue Kang +2
The matrix contextual bandit (CB), as an extension of the well-known multi-armed bandit, is a powerful framework that has been widely applied in sequential decision-making scenario…
Single Index Bandits: Generalized Linear Contextual Bandits with Unknown Reward Functions
Yue Kang, Mingshuo Liu, Bongsoo Yi +4
Generalized linear bandits have been extensively studied due to their broad applicability in real-world online decision-making problems. However, these methods typically assume tha…
Quantum Lipschitz Bandits
Bongsoo Yi, Yue Kang, Yao Li
The Lipschitz bandit is a key variant of stochastic bandit problems where the expected reward function satisfies a Lipschitz condition with respect to an arm metric space. With its…
Biased Dueling Bandits with Stochastic Delayed Feedback
Bongsoo Yi, Yue Kang, Yao Li
The dueling bandit problem, an essential variation of the traditional multi-armed bandit problem, has become significantly prominent recently due to its broad applications in onlin…