About me

I am now a postdoctoral fellow working with Prof. John C.S. Lui at The Chinese University of Hong Kong. I received my Ph.D. degree in Computer Science supervised by Prof. John C.S. Lui at The Chinese University of Hong Kong (CUHK) in 2022. Prior to that, I received my bachelor’s degree with honered rank (top 5% students) in the Department of Computer Science and Technology from University of Science and Technology of China (USTC) in 2017.

My major interests are machine learning theory as well as stochastic modeling to solve online combinatorial optimization problems. In particular, combinatorial multi-armed bandit and distributed/federated multi-armed bandit are my recent research focus. In addition, I am interested in network science, including research in social networks.

My CV is here/这里.

More about me can be found in [wiki][google scholar].

Working Paper

  • Constraint-aware Combinatorial Multi-Armed Bandits: A Relaxation and Rounding Approach.
    Xutong Liu, Ruofeng Yang, Shuai Li, Hong Xie, John C.S. Lui.
    [One-shot revision to SIGMETRICS 2022]

  • DCM-TS: Online Learning to Rank with Multiple Clicks via Thompson Sampling.
    Xutong Liu, Shuai Li, John C.S. Lui.
    [Under Submission]

Conference Paper

  • Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms.
    Xutong Liu, Jinhang Zuo, Siwei Wang, Carlee Joe-Wong, John C.S. Lui, Wei Chen.
    [To appear in Thirty-sixth Conference on Neural Information Processing Systems, NeurIPS, 2022] (2665/10411=25.6%)
    [arXiv]
  • Federated Online Clustering of Bandits.
    Xutong Liu, Haoru Zhao, Tong Yu, Shuai Li, John C.S. Lui.
    [The 38th Conference on Uncertainty in Artificial Intelligence, UAI, 2022.] (230/712=32%)
    [link] [arXiv] [poster] [code]

  • Online Competitive Influence Maximization.
    Jinhang Zuo, Xutong Liu, Carlee Joe-Wong, John C.S. Lui, Wei Chen.
    [The 25th International Conference on Artificial Intelligence and Statistics, AISTATS 2022] (492/1685=29%)
    [link] [arXiv]

  • Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning.
    Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C.S. Lui.
    [The 38th International Conference on Machine Learning, ICML (Long Oral), 2021.] (166/5513=3%)
    [link] [slides] [poster] [video] [arXiv]

  • Graphlet Count Estimation via Convolutional Neural Networks.
    Xutong Liu, Yu-Zhen Chen, John C.S. Lui, Konstantin Avrachenkov.
    COMPLEX NETWORKS, 2018.
    [PDF]

  • An Online Learning Approach to Network Application Optimization with Guarantee.
    Kechao Cai, Xutong Liu, Yuzhen Janice Chen, and John C.S. Lui.
    IEEE International Conference on Computer Communications (INFOCOM), 2018.
    [PDF]

Journal Paper

  • Learning with Guarantee via Constrained Multi-armed Bandit: Theory and Network Applications.
    Kechao Cai, Xutong Liu, Yuzhen Janice Chen, and John C.S. Lui.
    IEEE Transactions on Mobile Computing (IEEE TMC), 2022.
    DOI: https://doi.org/10.1109/TMC.2022.3173792

  • Learning to Count: a Deep Learning Framework for Graphlet Count Estimation.
    Xutong Liu, Yu-Zhen Chen, John C.S. Lui., Konstantin Avrachenkov.
    Network Science Journal.
    DOI: https://doi.org/10.1017/nws.2020.35.

Professional Services

Awards

  • Top 10% of reviewers at ICML 2022 [link]

Conference Reviewer for

  • Conference on Neural Information Processing Systems (NeurIPS) 2022
  • International Conference on Machine Learning (ICML) 2022
  • Conference on Uncertainty in Artificial Intelligence (UAI) 2021
  • International Conference on Artificial Intelligence and Statistics (AISTATS) 2022

Journal Reviewer for

  • IEEE Transactions on Network Science and Engineering

Working Experience

Jun. 2019 - Sep. 2019
Microsoft Research Asia (MSRA) - Theory Group, Research Intern, mentored by Wei Chen.

Sep. 2016 - Jan. 2017
Microsoft - CJK Applied Science Team, Data Scientist Intern, mentored by Nicholas Jing Yuan.

Teaching

CSCI-2040 Introduction to Python.
CSCI-3320 Foundamentals of Machine Learning.

Courses

ENGG-5501 Foundation of Optimization.
IERG-5130 Probabilistic Models and Inference Algorithms for Machine Learning.
CSCI-5160 Advanced Algorithms.
STAT-5020 Topics in Multivariate Analysis.
IERG 5330 Network Economics.
CSCI-5320 Topics in Graph Algorithms.
SEEM-5380 Optimization Methods in High Dimension Statistics.

Hobbies

In my spare time, I love playing basketball and I am a big fan of KING JAMES (that is why I choose “James” as my English name). Music is one of my hobbies. I like listening to all kinds of music and can play a little guitar, ukelele and piano.

Contact

Email:
liuxt2371 AT gmail DOT com
Address:
Rm.120, SHB, CUHK, Shatin, N.T., Hongkong.