A Markov Chain Monte Carlo Approach for Source Detection in Networks. - Le Zhang 010; Tianyuan Jin; Tong Xu 001; Biao Chang; Zhefeng Wang 001; Enhong Chen (SMP, 2017)

Maximizing the Effect of Information Adoption: A General Framework. - Tianyuan Jin; Tong Xu 001; Hui Zhong; Enhong Chen; Zhefeng Wang 001; Qi Liu 003 (SDM, 2018)

Tracking Top-K Influential Vertices in Dynamic Networks. - Yu Yang 001; Zhefeng Wang 001; Tianyuan Jin; Jian Pei 001; Enhong Chen (CoRR, 2018)

Tracking Top-k Influential Users with Relative Errors. - Yu Yang 001; Zhefeng Wang 001; Tianyuan Jin; Jian Pei 001; Enhong Chen (CIKM, 2019)

Efficient Pure Exploration in Adaptive Round model. - Tianyuan Jin; Jieming Shi 001; Xiaokui Xiao; Enhong Chen (NeurIPS, 2019)

Realtime Top-k Personalized PageRank over Large Graphs on GPUs. - Jieming Shi 001; Renchi Yang; Tianyuan Jin; Xiaokui Xiao; Yin Yang 001 (Proc. VLDB Endow., 2019)

Realtime Index-Free Single Source SimRank Processing on Web-Scale Graphs. - Jieming Shi 001; Tianyuan Jin; Renchi Yang; Xiaokui Xiao; Yin Yang 001 (Proc. VLDB Endow., 2020)

Double Explore-then-Commit: Asymptotic Optimality and Beyond. - Tianyuan Jin; Pan Xu 002; Xiaokui Xiao; Quanquan Gu (COLT, 2021)

MOTS: Minimax Optimal Thompson Sampling. - Tianyuan Jin; Pan Xu 002; Jieming Shi 001; Xiaokui Xiao; Quanquan Gu (ICML, 2021)

Optimal Streaming Algorithms for Multi-Armed Bandits. - Tianyuan Jin; Keke Huang; Jing Tang 004; Xiaokui Xiao (ICML, 2021)

Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits. - Tianyuan Jin; Jing Tang 004; Pan Xu 002; Keke Huang; Xiaokui Xiao; Quanquan Gu (ICML, 2021)

Unconstrained Submodular Maximization with Modular Costs: Tight Approximation and Application to Profit Maximization. - Tianyuan Jin; Yu Yang 001; Renchi Yang; Jieming Shi 001; Keke Huang; Xiaokui Xiao (Proc. VLDB Endow., 2021)

Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits. - Tianyuan Jin; Pan Xu 002; Xiaokui Xiao; Anima Anandkumar (NeurIPS, 2022)

Thompson Sampling with Less Exploration is Fast and Optimal. - Tianyuan Jin; Xianglin Yang; Xiaokui Xiao; Pan Xu 002 (ICML, 2023)

Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs. - Tianyuan Jin; Hao-Lun Hsu; William Chang; Pan Xu 002 (AAAI, 2024)

Optimal Batched Linear Bandits. - Xuanfei Ren; Tianyuan Jin; Pan Xu 002 (ICML, 2024)

Optimal Batched Best Arm Identification. - Tianyuan Jin; Yu Yang 001; Jing Tang 004; Xiaokui Xiao; Pan Xu 002 (NeurIPS, 2024)

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

Multi-Armed Bandits with Abstention. - Junwen Yang; Tianyuan Jin; Vincent Y. F. Tan (CoRR, 2024)

Best Arm Identification with Minimal Regret. - Junwen Yang; Vincent Y. F. Tan; Tianyuan Jin (CoRR, 2024)

Breaking the log⁡(1/Δ2) Barrier: Better Batched Best Arm Identification with Adaptive Grids. - Tianyuan Jin; Qin Zhang 001; Dongruo Zhou (ICLR, 2025)

Breaking the log(1/Δ2) Barrier: Better Batched Best Arm Identification with Adaptive Grids. - Tianyuan Jin; Qin Zhang 001; Dongruo Zhou (CoRR, 2025)

Calibrating LLM Confidence with Semantic Steering: A Multi-Prompt Aggregation Framework. - Ziang Zhou; Tianyuan Jin; Jieming Shi 001; Qing Li 001 (CoRR, 2025)