Jin, Tianyuan

13 publications

ICLR 2025 Breaking the $\log(1/\Delta_2)$ Barrier: Better Batched Best Arm Identification with Adaptive Grids Tianyuan Jin, Qin Zhang, Dongruo Zhou

NeurIPS 2025 SteerConf: Steering LLMs for Confidence Elicitation Ziang Zhou, Tianyuan Jin, Jieming Shi, Li Qing

AAAI 2024 Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs Tianyuan Jin, Hao-Lun Hsu, William Chang, Pan Xu

NeurIPS 2024 Optimal Batched Best Arm Identification Tianyuan Jin, Yu Yang, Jing Tang, Xiaokui Xiao, Pan Xu

ICML 2024 Optimal Batched Linear Bandits Xuanfei Ren, Tianyuan Jin, Pan Xu

NeurIPS 2024 Sparsity-Agnostic Linear Bandits with Adaptive Adversaries Tianyuan Jin, Kyoungseok Jang, Nicolò Cesa-Bianchi

ICML 2023 Thompson Sampling with Less Exploration Is Fast and Optimal Tianyuan Jin, Xianglin Yang, Xiaokui Xiao, Pan Xu

NeurIPS 2022 Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits Tianyuan Jin, Pan Xu, Xiaokui Xiao, Anima Anandkumar

ICML 2021 Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits Tianyuan Jin, Jing Tang, Pan Xu, Keke Huang, Xiaokui Xiao, Quanquan Gu

COLT 2021 Double Explore-Then-Commit: Asymptotic Optimality and Beyond Tianyuan Jin, Pan Xu, Xiaokui Xiao, Quanquan Gu

ICML 2021 MOTS: Minimax Optimal Thompson Sampling Tianyuan Jin, Pan Xu, Jieming Shi, Xiaokui Xiao, Quanquan Gu

ICML 2021 Optimal Streaming Algorithms for Multi-Armed Bandits Tianyuan Jin, Keke Huang, Jing Tang, Xiaokui Xiao

NeurIPS 2019 Efficient Pure Exploration in Adaptive Round Model Tianyuan Jin, Jieming Shi, Xiaokui Xiao, Enhong Chen