Tianyuan Jin

According to our database, Tianyuan Jin authored at least 20 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Best Arm Identification with Minimal Regret.

Junwen Yang, Vincent Y. F. Tan, Tianyuan Jin

CoRR, 2024

Sparsity-Agnostic Linear Bandits with Adaptive Adversaries.

Tianyuan Jin, Kyoungseok Jang, Nicolò Cesa-Bianchi

CoRR, 2024

Multi-Armed Bandits with Abstention.

Junwen Yang, Tianyuan Jin, Vincent Y. F. Tan

CoRR, 2024

Optimal Batched Linear Bandits.

Xuanfei Ren, Tianyuan Jin, Pan Xu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.

Tianyuan Jin, Hao-Lun Hsu, William Chang, Pan Xu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Optimal Batched Best Arm Identification.

Tianyuan Jin, Yu Yang, Jing Tang, Xiaokui Xiao, Pan Xu

CoRR, 2023

Thompson Sampling with Less Exploration is Fast and Optimal.

Tianyuan Jin, Xianglin Yang, Xiaokui Xiao, Pan Xu

Proceedings of the International Conference on Machine Learning, 2023

2022

Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits.

Tianyuan Jin, Pan Xu, Xiaokui Xiao, Anima Anandkumar

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Unconstrained Submodular Maximization with Modular Costs: Tight Approximation and Application to Profit Maximization.

Tianyuan Jin, Yu Yang, Renchi Yang, Jieming Shi, Keke Huang, Xiaokui Xiao

Proc. VLDB Endow., 2021

Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits.

Tianyuan Jin, Jing Tang, Pan Xu, Keke Huang, Xiaokui Xiao, Quanquan Gu

Proceedings of the 38th International Conference on Machine Learning, 2021

Optimal Streaming Algorithms for Multi-Armed Bandits.

Tianyuan Jin, Keke Huang, Jing Tang, Xiaokui Xiao

Proceedings of the 38th International Conference on Machine Learning, 2021

MOTS: Minimax Optimal Thompson Sampling.

Tianyuan Jin, Pan Xu, Jieming Shi, Xiaokui Xiao, Quanquan Gu

Proceedings of the 38th International Conference on Machine Learning, 2021

Double Explore-then-Commit: Asymptotic Optimality and Beyond.

Tianyuan Jin, Pan Xu, Xiaokui Xiao, Quanquan Gu

Proceedings of the Conference on Learning Theory, 2021

2020

Realtime Index-Free Single Source SimRank Processing on Web-Scale Graphs.

Jieming Shi, Tianyuan Jin, Renchi Yang, Xiaokui Xiao, Yin Yang

Proc. VLDB Endow., 2020

2019

Realtime Top-k Personalized PageRank over Large Graphs on GPUs.

Jieming Shi, Renchi Yang, Tianyuan Jin, Xiaokui Xiao, Yin Yang

Proc. VLDB Endow., 2019

Efficient Pure Exploration in Adaptive Round model.

Tianyuan Jin, Jieming Shi, Xiaokui Xiao, Enhong Chen

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Tracking Top-k Influential Users with Relative Errors.

Yu Yang, Zhefeng Wang, Tianyuan Jin, Jian Pei, Enhong Chen

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2018

Tracking Top-K Influential Vertices in Dynamic Networks.

Yu Yang, Zhefeng Wang, Tianyuan Jin, Jian Pei, Enhong Chen

CoRR, 2018

Maximizing the Effect of Information Adoption: A General Framework.

Tianyuan Jin, Tong Xu, Hui Zhong, Enhong Chen, Zhefeng Wang, Qi Liu

Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

2017

A Markov Chain Monte Carlo Approach for Source Detection in Networks.

Le Zhang, Tianyuan Jin, Tong Xu, Biao Chang, Zhefeng Wang, Enhong Chen

Proceedings of the Social Media Processing - 6th National Conference, 2017