Tianyuan Jin

Bio

I am a second year PhD student in the School of Computing at the National University of Singapore. I am very fortunate to be advised by Prof. Xiaokui Xiao.
Prior to that, I obtained my master degree in computer science at University of Science and Technology of China and my bachelor's degree in mathematics at
University of Science and Technology of China. My master work was advised by Prof. Enhong Chen.

Contact

Email: tianyuan@u.nus.edu

Selected Papers

* stands for the equal contribution.

• Double Explore-then-Commit: Asymptotic Optimality and Beyond
  Tianyuan Jin, Pan Xu, Xiaokui Xiao, Quanquan Gu
  Proceedings of the Annual Conference on Learning Theory (COLT 2021), to appear. [arXiv]

• MOTS: Minimax Optimal Thompson Sampling
  Tianyuan Jin, Pan Xu, Jieming Shi, Xiaokui Xiao, Quanquan Gu
  Proceedings of the International Conference on Machine Learning (ICML 2021), to appear. [arXiv]

• Optimal Streaming Algorithms for Multi-Armed Bandits
  Tianyuan Jin, Keke Huang, Jing Tang, Xiaokui Xiao
  Proceedings of the International Conference on Machine Learning (ICML 2021), to appear.

• Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits
  Tianyuan Jin, Jing Tang, Pan Xu, Keke Huang, Xiaokui Xiao, Quanquan Gu
  Proceedings of the International Conference on Machine Learning (ICML 2021), to appear.

• 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
  Proceedings of the VLDB Endowment (PVLDB 2021), to appear.
  This work has been presented at the ICML 2021 Subset Selection in Machine Learning: From Theory to Practice Workshop.

• Realtime Index-Free Single Source SimRank Processing on Web-Scale Graphs
  Jieming Shi*, Tianyuan Jin*,, Renchi Yang, Xiaokui Xiao, Yin Yang
  Proceedings of the VLDB Endowment (PVLDB 2020)), 13(7): 966-978, 2020.

• Efficient Pure Exploration in Adaptive Round model
  Tianyuan Jin, Jieming Shi, Xiaokui Xiao, Enhong Chen
  Proceedings of the Advances in Neural Information Processing Systems (NeurIPS), pages 2041-2049, 2019.

Research Interests

• Machine Learning

• Online Learning and Bandits

• Submodularity

• Graph Algorithms