Vincent Y. F. Tan 陈延福 (Pronouns: he/him/his/他)

Images courtesy of Dave Lee (UCO, NUS)

Professor, Department of Mathematics, Department of Electrical and Computer Engineering (ECE), National University of Singapore (NUS) Affiliate, Institute of Operations Research and Analytics (IORA), Institute of Data Science (IDS) Office: S17-05-20 (Mathematics) and E4-06-06 (ECE) Phone: (65) 6516-2133 Email: vtan @ nus. edu. sg My Curriculum Vitae. My Google Scholar Profile. My Erdős number is 3 (Tan -> Willsky -> Bollobás -> Erdős).

News (Archive)

• Advertisement: Looking to hire motivated postdocs. Please see this advertisement for more details.


• Apr 2024: Paper "A Hybrid Genetic Search and Dynamic Programming-based Split Algorithm for the Multi-trip Time-dependent Vehicle Routing Problem" accepted by the European Journal of Operations Research (EJOR). Congrats to former Ph.D. student Jingyi Zhao and collaborators Mark Poon and Zhenzhen Zhang. My first paper in EJOR.


• Apr 2024: Three papers accepted to ISIT 2024 in Athens, Greece. (i) "Optimal Private Discrete Distribution Estimation with One-bit Communication" with Seung-Hyun Nam and Si-Hyeon Lee; (ii) "Best Arm Identification with Arm Erasures" with former postdocs Srinivas Kota Reddy and P. N. Karthik and (iii) "Robust Distributed Gradient Descent to Corruption over Noisy Channels" with Ph.D. student Shuche Wang.


• Mar 2024: Paper on Indexed Minimum Empirical Divergence-Based Algorithms for Linear Bandits the Transactions on Machine Learning Research. Joint work with Ph.D. student Jie Bian. In this paper, we extend the IMED algorithm so that it is amenable to stochastic linear bandits. We show a state-of-the-art regret bound. Congrats Jie Bian!


• Mar 2024: Paper on Adversarial Combinatorial Bandits with Switching Costs accepted to the IEEE Transactions on Information Theory. Joint work with former postdoc Yanyan Dong. In this paper, we consider the adversarial combinational bandits problem where the switch of each selected arm in each round incurs a fixed cost. We quantify the regret in the semi-bandit and bandit feedback settings. Congrats Yanyan!


• Feb 2024: Paper on DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editing accepted to CVPR 2024 in Seattle and to be presented as a spotlight poster! Congrats to Yujun Shi and all co-authors. In this paper, we enable "drag" editing on diffusion models. By leveraging large-scale pre-trained diffusion models, we greatly improve the generality of "drag" editing.


• Feb 2024: Posted a paper on Multi-Armed Bandits with Abstention. Joint work with Junwen Yang and Tianyuan Jin.


• Feb 2024: Traveling to San Diego for ITA 2024. Here are my slides.


• Feb 2024: Invited to deliver a plenary talk at ISITA 2024.


• Jan 2024: Posted a paper on Variable-Length Feedback Codes over Known and Unknown Channels with Non-vanishing Error Probabilities. Joint work with Recep Can Yavas.


• Jan 2024: Paper on Fixed-Budget Best Arm Identification in Sparse Linear Bandits accepted to the Transactions on Machine Learning Research. Congrats to Recep!


• Jan 2024: Received the Faculty of Science "Faculty Award for Mentorship Excellence (Research Category)".
  
  
  


• Jan 2024: Posted a paper on Fixed-Budget Differentially Private Best Arm Identification. This is joint work with ISEM Ph.D. student Zhirui Chen, postdoc P. N. Karthik and ISEM collaborator Yeow Meng Chee. In this paper, we address the problem of best arm identification in the fixed-budget setting under differential privacy constraints, considering the notion of ε-differential privacy and provide guarantees on the error probability. This paper will be presented at the upcoming ICLR in Vienna.


• Jan 2024: Three papers accepted at the 2024 International Conference on Learning Representations (ICLR). See CS Conference Papers for details.


• Jan 2024: Former Ph.D. student Zhaoqiang Liu and former postdoc Yonglong Li joined UESTC and Xi'an Jiaotong University, respectively, both as 优秀青年科学基金项目（海外）professors.


• Jan 2024: Invited to give a lecture in the General ML track at the Research Week at Google Research in Bangalore.


• Jan 2024: Rated 4.2/5.0 for my teaching of DSA3102 Convex Optimization last semester. See some review quotes here.


• Dec 2023: Posted a paper titled Towards Accurate Guided Diffusion Sampling through Symplectic Adjoint Method.


• Nov 2023: Paper on Federated Best Arm Identification with Heterogeneous Clients accepted to the IEEE Transactions on Information Theory. Congrats to Ph.D. student Zhirui Chen and postdoc P. N. Karthik. In this paper, we show, among other cool results, that for any algorithm whose upper bound on the expected time to find the best arms matches with the lower bound up to a multiplicative constant, the ratio of any two consecutive communication time instants must be bounded.


• Nov 2023: Paper on Understanding and Mitigating Dimensional Collapse in Federated Learning accepted to the IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI). Congrats to Ph.D. student Yujun Shi. This is the extended version of our ICLR 2023 paper.


• Nov 2023: Reelected to the IEEE Information Theory Society Board of Governors for a second term (2024 to 2026). Thanks all for the support!


• Nov 2023: Posted a paper on Fixed-Budget Best Arm Identification in Sparse Linear Bandits. Joint work with Recep Can Yavas.

Research Interests and Open Positions

Online Decision Making, Multi-Armed Bandits, Reinforcement Learning
Information Theory with Applications to Machine Learning
Statistical Signal Processing

I am actively recruiting graduate students in the areas of my research interest above. There are various channels to be admitted to NUS including to the Faculty of Science, the College of Design and Engineering, the Institute of Operations Research and Analytics, and the Integrative Sciences and Engineering Programme (Institute of Data Science).

There are also multiple positions for talented postdoctoral scholars. Postdoctoral scholars with strong publication records and showing interest in the above research topics are also encouraged to contact me to check with me if there are available positions. Please see this advertisement as well as this.

Selected Recent Publications

1. Indexed Minimum Empirical Divergence-Based Algorithms for Linear Bandits
   Jie Bian and Vincent Y. F. Tan
   Transactions on Machine Learning Research, 2024+

2. Adversarial Combinatorial Bandits with Switching Costs
   Yanyan Dong and Vincent Y. F. Tan
   IEEE Transactions on Information Theory, 2024+

3. Federated Best Arm Identification with Heterogeneous Clients
   Zhirui Chen, P. N. Karthik, Vincent Y. F. Tan, and Yeow Meng Chee
   IEEE Transactions on Information Theory, 2024+

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

Oldies But Goldies

1. Common Information, Noise Stability, and Their Extensions
   Lei Yu and Vincent Y. F. Tan
   Foundations and Trends® in Communications and Information Theory, Vol. 19, No. 2, Pages 107 - 389, 2022

2. Asymptotic Estimates in Information Theory with Non-Vanishing Error Probabilities
   Vincent Y. F. Tan
   Foundations and Trends® in Communications and Information Theory, Vol. 11, Nos. 1-2, Pages 1 – 184, 2014

3. Automatic Relevance Determination in Nonnegative Matrix Factorization with the β-Divergence [Slides] [Code]
   Vincent Y. F. Tan and Cédric Févotte
   IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 35, No. 7, Pages 1592 - 1605, Jul 2013

4. A Large-Deviation Analysis of the Maximum-Likelihood Learning of Markov Tree Structures [Slides]
   Vincent Y. F. Tan, Animashree Anandkumar, Lang Tong and Alan S. Willsky
   IEEE Transactions on Information Theory, Vol. 57, No. 3, Pages 1714 - 1735, Mar 2011

5. Estimating Signals with Finite Rate of Innovation from Noisy Samples: A Stochastic Algorithm [Code]
   Vincent Y. F. Tan and Vivek K Goyal
   IEEE Transactions on Signal Processing, Vol. 56, Issue 10, No. 5135 - 5145, Oct 2008