Vincent Liu
Vincent Liu

Machine Learning Researcher

RBC Borealis

About Me

I am a machine learning researcher at RBC Borealis. Previously, I was an instructor at the University of British Columbia, where I taught data science. I completed my PhD in Computing Science at the University of Alberta, advised by Professor Martha White. My primary research focuses on offline reinforcement learning, and I am broadly interested in applying machine learning and reinforcement learning to solve real-world decision-making problems.

Interests
  • Reinforcement Learning
  • Machine Learning
  • Data Science
Education

  • PhD in Statistical Machine Learning

    University of Alberta

  • MSc in Statistical Machine Learning

    University of Alberta

  • Bachelor of Business Administration

    National Taiwan University

Recent Publications
Alex Ayoub, Kaiwen Wang, Vincent Liu, Samuel Robertson, James McInerney, Dawen Liang, Nathan Kallus, Csaba Szepesvári (2024). Switching the Loss Reduces the Cost in Batch Reinforcement Learning. International Conference on Machine Learning.
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Han Wang, Erfan Miahi, Martha White, Marlos C Machado, Zaheer Abbas, Raksha Kumaraswamy, Vincent Liu, Adam White (2024). Investigating the properties of neural network representations in reinforcement learning. Artificial Intelligence.
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Vincent Liu, Prabhat Nagarajan, Andrew Patterson, Martha White (2023). When is Offline Policy Selection Feasible for Reinforcement Learning?. Under submission.
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Vincent Liu, James R Wright, Martha White (2023). Exploiting action impact regularity and exogenous state variables for offline reinforcement learning. Journal of Artificial Intelligence Research.
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Vincent Liu, Yash Chandak, Philip Thomas, Martha White (2023). Asymptotically Unbiased Off-Policy Policy Evaluation when Reusing Old Data in Nonstationary Environments. International Conference on Artificial Intelligence and Statistics.
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Vincent Liu, Han Wang, Ruo Yu Tao, Khurram Javed, White Adam, Martha White (2023). Measuring and Mitigating Interference in Reinforcement Learning. Conference on Lifelong Learning Agents.
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Han Wang, Archit Sakhadeo, Adam M White, James M Bell, Vincent Liu, Xutong Zhao, Puer Liu, Tadashi Kozuno, Alona Fyshe, Martha White (2022). No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL. Transactions on Machine Learning Research.
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Somjit Nath, Vincent Liu, Alan Chan, Adam White, Martha White (2020). Training Recurrent Neural Networks Online by Learning Explicit State Variables. International Conference on Learning Representations.
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Vincent Liu, Raksha Kumaraswamy, Lei Le, Martha White (2019). The utility of sparse representations for control in reinforcement learning. Proceedings of the AAAI Conference on Artificial Intelligence.
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Andrew Jacobsen, Vincent Liu, Roshan Shariff, Adam White, Martha White (2019). A Value Function Basis for Nexting and Multi-step Prediction. The Multi-disciplinary Conference on Reinforcement Learning and Decision Making.
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Brendan Bennett, Wesley Chung, Muhammad Zaheer, Vincent Liu (2019). Incrementally Learning Functions of the Return. The Multi-disciplinary Conference on Reinforcement Learning and Decision Making.
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Wen-Hao Chen, Chin-Chi Hsu, Yi-an Lai, Vincent Liu, Mi-Yen Yeh, Shou-De Lin (2019). Attribute-aware recommender system based on collaborative filtering: Survey and classification. Frontiers in big Data.
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Teaching

Instructor, University of British Columbia

  • DSCI 573 Feature and Model Selection, Fall 2024
  • DSCI 551 Descriptive Statistics and Probability for Data Science, Fall 2024
  • DSCI 512 Algorithms and Data Structures, Fall 2024

Teaching Assistant, University of Alberta

  • CMPUT 655 Reinforcement Learning I, Fall 2022
  • CMPUT 298 Basic of Machine Learning, Winter 2020
  • CMPUT 175 Introduction to the Foundations of Computation II, Fall 2017 and Winter 2018