Vincent Y. F. Tan

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Computer Science Conference Papers

  1. p-Mean Regret for Stochastic Bandits [Full Version on arXiv]
    Anand Krishna, Philips George John, Adarsh Barik, Vincent Y. F. Tan
    Proc. of the 39th AAAI Conference on Artificial Intelligence (AAAI), Philadelphia, PA, Feb 2025 (AR: 3032/12957 ≈ 23.4%)

  2. Almost Minimax Optimal Best Arm Identification in Piecewise Stationary Linear Bandits
    Yunlong Hou, Vincent Y. F. Tan, and Zixin Zhong
    Proc. of the 38th Annual Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, Dec 2024 (AR ≈ 25.8%)

  3. Influence Maximization via Graph Neural Bandits [Code] [Video]
    Yuting Feng, Vincent Y. F. Tan, and Bogdan Cautis
    Proc. of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Barcelona, Spain, Aug 2024 (AR ≈ 20%)

  4. DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editing [Project Page] [Video]
    Yujun Shi, Chuhui Xue, Jun Hao Liew, Jiachun Pan, Hanshu Yan, Wenqing Zhang, Vincent Y. F. Tan, and Song Bai (Spotlight)
    Proc. of the Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, Jun 2024 (AR ≈ 23.6%, Highlight ≈ 11.9% of Accepted Papers)

  5. Fixed-Budget Differentially Private Best Arm Identification [Slides]
    Zhirui Chen, P. N. Karthik, Yeow Meng Chee, and Vincent Y. F. Tan
    Proc. of the 12th International Conference on Learning Representations (ICLR), Vienna, Austria, May 2024 (AR ≈ 31%)

  6. Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes
    Ruiquan Huang, Yuan Cheng, Jing Yang, Vincent Y. F. Tan, and Yingbin Liang
    Proc. of the 12th International Conference on Learning Representations (ICLR), Vienna, Austria, May 2024 (AR ≈ 31%)

  7. AdjointDPM: Adjoint Sensitivity Method for Gradient Backpropagation of Diffusion Probabilistic Models
    Jiachun Pan, Hanshu Yan, Jun Hao Liew, Vincent Y. F. Tan, and Jiashi Feng
    Proc. of the 12th International Conference on Learning Representations (ICLR), Vienna, Austria, May 2024 (AR ≈ 31%)

  8. Learning Regularized Monotone Graphon Mean-Field Games
    Fengzhuo Zhang, Vincent Y. F. Tan, Zhuoran Yang, and Zhaoran Wang
    Proc. of the 37th Annual Conference on Neural Information Processing Systems (NeurIPS), New Orleans, USA, Dec 2023 (AR ≈ 26.1%)

  9. BLINK: Link Local Differential Privacy for Graph Neural Networks via Bayesian Estimation
    Xiaochen Zhu, Vincent Y. F. Tan, and Xiaokui Xiao
    Proc. of the ACM SIGSAC Conference on Computer and Communications Security (CCS), Copenhagen, Denmark, Nov 2023 (AR = 234/1222 ≈ 19.15%)

  10. Probably Anytime-Safe Stochastic Combinatorial Semi-Bandits [Video]
    Yunlong Hou, Vincent Y. F. Tan, and Zixin Zhong
    Proc. of the 40th International Conference on Machine Learning (ICML), Hawaii, Jul 2023 (AR: 1827/6538 ≈ 27.9%)

  11. Communication-Constrained Bandits under Additive Gaussian Noise
    Prathamesh Mayekar, Jonathan Scarlett, and Vincent Y. F. Tan
    Proc. of the 40th International Conference on Machine Learning (ICML), Hawaii, Jul 2023 (AR: 1827/6538 ≈ 27.9%)

  12. Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation [Code]
    Jiawei Du, Yidi Jiang, Vincent Y. F. Tan, Joey Tianyi Zhou, and Haizhou Li
    Proc. of the Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Jun 2023 (AR: 2360/9155 ≈ 25.78%)

  13. Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning
    Yujun Shi, Jian Liang, Wenqing Zhang, Vincent Y. F. Tan, and Song Bai
    Proc. of the 11th International Conference on Learning Representations (ICLR), Kigali, Rwanda, May 2023 (AR ≈ 31.8%)

  14. How Does Pseudo-Labeling Affect the Generalization Error of the Semi-Supervised Gibbs Algorithm? [Video]
    Haiyun He, Gholamali Aminian, Yuheng Bu, Miguel R. D. Rodrigues, and Vincent Y. F. Tan
    Proc. of 26th International Conference on Artificial Intelligence and Statistics (AISTATS), Valencia, Spain, Apr 2023 (AR ≈ 29%)

  15. Almost Cost-Free Communication in Federated Best Arm Identification
    Kota Srinivas Reddy, P. N. Karthik, and Vincent Y. F. Tan
    Proc. of the 37th AAAI Conference on Artificial Intelligence, 37(7), 8378 - 8385, Washington DC, Feb 2023 (AR: 1721/8777 ≈ 19.6%)

  16. Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL
    Fengzhuo Zhang, Boyi Liu, Kaixin Wang, Vincent Y. F. Tan, Zhuoran Yang, and Zhaoran Wang
    Proc. of the 36th Annual Conference on Neural Information Processing Systems (NeurIPS), New Orleans, USA, Dec 2022 (AR ≈ 25.6%)

  17. Minimax Optimal Fixed-Budget Best Arm Identification in Linear Bandits
    Junwen Yang and Vincent Y. F. Tan
    Proc. of the 36th Annual Conference on Neural Information Processing Systems (NeurIPS), New Orleans, USA, Dec 2022 (AR ≈ 25.6%)

  18. Sharpness-Aware Training for Free
    Jiawei Du, Daquan Zhou, Jiashi Feng, Vincent Y. F. Tan, and Joey Tianyi Zhou
    Proc. of the 36th Annual Conference on Neural Information Processing Systems (NeurIPS), New Orleans, USA, Dec 2022 (AR ≈ 25.6%)

  19. Towards Adversarially Robust Deep Image Denoising
    Hanshu Yan, Jingfeng Zhang, Jiashi Feng, Masashi Sugiyama, and Vincent Y. F. Tan
    Proc. of the 31st International Joint Conference on Artificial Intelligence (IJCAI), Vienna, Austria, Aug 2022 (AR ≈ 15%)

  20. A Survey of Risk-Aware Multi-Armed Bandits [Full Version] [Slides]
    Vincent Y. F. Tan, Prashanth L. A., and Krishna Jagannathan
    Proc. of the 31st International Joint Conference on Artificial Intelligence (IJCAI) (Survey Track), Vienna, Austria, Aug 2022 (AR: 38/209 ≈ 18.2%)

  21. Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning
    Yujun Shi, Kuangqi Zhou, Jian Liang, Zihang Jiang, Jiashi Feng, Philip Torr, Song Bai, and Vincent Y. F. Tan
    Proc. of the Conference on Computer Vision and Pattern Recognition (CVPR), New Orleans, USA, Jun 2022 (AR: 2067/8161 ≈ 25.33%)

  22. Efficient Sharpness-aware Minimization for Improved Training of Neural Networks
    Jiawei Du, Hanshu Yan, Jiashi Feng, Joey Tianyi Zhou, Liangli Zhen, Rick Siow Mong Goh, and Vincent Y. F. Tan
    Proc. of the 10th International Conference on Learning Representations (ICLR), Virtual, Apr 2022 (AR: 1095/3391 ≈ 32.3%)

  23. A Unifying Theory of Thompson Sampling for Continuous Risk-Averse Bandits [Code]
    Joel Q. L. Chang and Vincent Y. F. Tan (Oral Presentation)
    Proc. of the 36th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, BC, Canada, Feb 2022 (AR: 1349/9020 ≈ 15.0%)

  24. Robustifying Latent Tree Learning Algorithms with Vector Variables [Video]
    Fengzhuo Zhang and Vincent Y. F. Tan
    Proc. of the 35th Annual Conference on Neural Information Processing Systems (NeurIPS), Virtual, Dec 2021 (AR: 2344/9122 ≈ 25.7%)

  25. Probabilistic Sequential Shrinking: A Best Arm Identification Algorithm for Stochastic Bandits with Corruptions [Code] [Video]
    Zixin Zhong, Wang Chi Cheung, and Vincent Y. F. Tan
    Proc. of the 38th International Conference on Machine Learning (ICML), Virtual, Jul 2021 (AR: 1184/5513 ≈ 21.5%)

  26. CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection
    Hanshu Yan, Jingfeng Zhang, Gang Niu, Jiashi Feng, Vincent Y. F. Tan, and Masashi Sugiyama
    Proc. of the 38th International Conference on Machine Learning (ICML), Virtual, Jul 2021 (AR: 1184/5513 ≈ 21.5%)

  27. SGA: A Robust Algorithm for Partial Recovery of Tree-Structured Graphical Models with Noisy Samples [Slides] [Poster] [Code] [Video]
    Anshoo Tandon, Aldric J. Y. Han and Vincent Y. F. Tan
    Proc. of the 38th International Conference on Machine Learning (ICML), Virtual, Jul 2021 (AR: 1184/5513 ≈ 21.5%)

  28. Thompson Sampling Algorithms for Mean-Variance Bandits [Code] [Video]
    Qiuyu Zhu and Vincent Y. F. Tan
    Proc. of the 37th International Conference on Machine Learning (ICML), Vienna, Austria, Jul 2020 (AR: 1088/4990 ≈ 21.8%)

  29. Best Arm Identification for Cascading Bandits in the Fixed Confidence Setting
    Zixin Zhong, Wang Chi Cheung, and Vincent Y. F. Tan
    Proc. of the 37th International Conference on Machine Learning (ICML), Vienna, Austria, Jul 2020 (AR: 1088/4990 ≈ 21.8%)

  30. Economy Statistical Recurrent Units for Inferring Nonlinear Granger Causality
    Saurabh Khanna and Vincent Y. F. Tan
    Proc. of the 8th International Conference on Learning Representations (ICLR), Addis Ababa, Apr 2020 (AR: 687/2594 ≈ 26.5%)

  31. On Robustness of Neural Ordinary Differential Equations
    Hanshu Yan, Jiawei Du, Vincent Y. F. Tan, and Jiashi Feng (Spotlight)
    Proc. of the 8th International Conference on Learning Representations (ICLR), Addis Ababa, Apr 2020 (AR: 687/2594 ≈ 26.5%)

  32. Mobile Gait Analysis using Foot-Mounted UWB Sensors
    Boyd Anderson, Mingqian Shi, Vincent Y. F. Tan and Wang Ye
    Proc. of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), Vol. 3, Issue 3, Sep 2019

  33. A Ranking Model Motivated by Nonnegative Matrix Factorization with Applications to Tennis Tournaments [Slides]
    Rui Xia, Vincent Y. F. Tan, Louis Filstroff, and Cédric Févotte
    Proc. of European Conference on Machine Learning (ECML/PKDD), 2019 (AR: 130/734 ≈ 17.7%)

  34. Thompson Sampling for Cascading Bandits [Slides]
    Wang Chi Cheung, Vincent Y. F. Tan, and Zixin Zhong (Oral Presentation)
    Proc. of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 2019, Naha, Okinawa, Japan (AR: 360/1111 ≈ 32.4%)

  35. An Optimal Algorithm for Stochastic Three-Composite Optimization
    Renbo Zhao, William B. Haskell and Vincent Y. F. Tan
    Proc. of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 2019, Naha, Okinawa, Japan (AR: 360/1111 ≈ 32.4%)

  36. MANA: Designing And Validating A User-Centered Mobility Analysis System
    Boyd Anderson, Shenggao Zhu, Ke Yang, Jian Wang, Hugh Anderson, Chao Xu Tay, Vincent Y. F. Tan and Wang Ye
    Proc. of the 20th Intl. ACM SIGACCESS Conference on Computers and Accessibility (ASSETS), 2018, Galway, Ireland

  37. Stochastic L-BFGS Revisited: Improved Convergence Rates and Practical Acceleration Strategies [News]
    Renbo Zhao, William B. Haskell and Vincent Y. F. Tan
    Proc. of the 33rd Uncertainty in Artificial Intelligence (UAI) Conference, 2017, Sydney, Australia (AR: 87/282 ≈ 30.9%)

  38. Online Nonnegative Matrix Factorization with General Divergences [Slides]
    Renbo Zhao, Vincent Y. F. Tan and Huan Xu
    Proc. of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS), 2017, Fort Lauderdale, FL, USA (AR: 168/530 ≈ 31.7%)

  39. Rényi Resolvability and Its Applications to the Wiretap Channel
    Lei Yu and Vincent Y. F. Tan
    Proc. of the 10th International Conference on Information Theoretic Security (ICITS), 2017, Hong Kong

  40. High-Dimensional Graphical Model Selection: Tractable Graph Families and Necessary Conditions
    Animashree Anandkumar, Vincent Y. F. Tan, and Alan S. Willsky
    Proc. of the 25th Annual Conference on Neural Information Processing Systems (NIPS) 2011, Granada, Spain (AR ≈ 21.8%)