Martha White
Appointment
Fellow
Canada CIFAR AI Chair
Learning in Machines & Brains
Pan-Canadian AI Strategy
About
Appointed Canada CIFAR AI Chair – 2018
Renewed Canada CIFAR AI Chair – 2023
Martha White is a Canada CIFAR AI Chair, a fellow at Amii, and an Associate professor in the Department of Computing Science at the University of Alberta.
White’s research seeks to advance representation learning for reinforcement learning. Her primary research goal is to develop techniques for adaptive autonomous agents learning on streams of data. Her research approach focuses on principled optimization approaches for representation learning, particularly looking at sparse representations and recurrent architectures for partially observable domains. White has also been working on off-policy reinforcement learning, which enables learning about many different policies in parallel from a single stream of interaction with the environment.
Awards
- Canada Research Chair Tier II, 2024
- AI Researcher of the Year Award, Women in AI Awards North America, 2023
- Faculty of Science Research Award, University of Alberta, 2022
- IEEE AI’s 10 to Watch: The Future of AI, 2020
Relevant Publications
- Janjua, K., Shah, H., White, M., Miahi, E., Machado, M.C. & White, A. (2023). GVFs in the Real World: Making Predictions Online for Water Treatment. Machine Learning (MLJ).
- Graves, E., Imani, E., Kumaraswamy, R. & White, M. (2023). Off-Policy Actor-Critic with Emphatic Weightings. Journal of Machine Learning Research (JMLR).
- Neumann, S., Lim, S., Joseph, A.G., Pan, Y., White, A. and White, M. Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement. (2023) International Conference on Representation Learning (ICLR).
- Patterson, A., White, A., & White, M. (2022). A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning. Journal of Machine Learning Research.
Pan, Y., Banman, K., & White, M. (2021). Fuzzy Tiling Activations: A Simple Approach to Learning Sparse Representations Online. International Conference on Learning Representations.