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Calgary ML Lab

The Calgary Machine Learning Lab is a research group led by Yani Ioannou within the Schulich School of Engineering at the University of Calgary. The lab has a research focus on improving Deep Neural Network (DNN) training and models, in particular for computer vision applications. Topics of research include: Sparse Neural Network Training, Bias and Robustness of Efficient Deep Learning methods and Domain-Agnostic Self-Supervised Learning.

We collaborate with other research groups within the university with the Artificial Intelligence Research Group, and broader, on applying machine learning and computer vision to novel problems.

news

Nov 25, 2022 We have been awarded an Alberta Innovates Advance, Stream II/NSERC Alliance grant for our research project investigating learning structure in neural networks for novel data domains over the next two years. Alberta Innovates Advance invests in projects that, in alignment with Alberta’s technology and innovation strategies, advance discoveries to develop emerging technologies which can generate economic, environmental, health and social benefits for Albertans and Canadians.
Oct 11, 2022 We have been awarded an Amazon Research Award — a highly competitive international awarded based on the merit of a research proposal. Our research proposal “Addressing Catastrophic Forgetting with Dynamic Sparse Training” proposes to explore the effect of dynamic sparse training on catastrophic forgetting.
Sep 1, 2022 Our newest lab member, Aida Mohammadshahi, has been awarded an Alberta Graduate Excellence Scholarship (AGES) to support her MSc. studies. The AGES scholarships are awarded to students enrolled in an Alberta-based Graduate degree, and are based on outstanding academic achievement.
Aug 30, 2022 We have been awarded a 2022 National Sciences and Engineering Research Council of Canada (NSERC) and Department’s of National Defence (DND) Discovery Grant Supplement — one of only 20 awarded nationally! This supplement will help accelerate our research over the next 3 years.
Jul 13, 2022 Our workshop paper, (Golubeva et al., 2022), was accepted at the 2nd Sparsity in Neural Networks workshop.

selected publications

  1. Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win
    Evci, UtkuIoannou, Yani A.Keskin, Cem, and Dauphin, Yann
    In Proceedings of the 36th AAAI Conference on Artificial Intelligence, Vancouver, BC, Canada Feb 2022
  2. Domain-Agnostic Clustering with Self-Distillation
    Adnan, Mohammed,  Ioannou, Yani, Tsai, Chuan-Yung, and Taylor, Graham
    In 2nd NeurIPS Workshop on Self-Supervised Learning: Theory and Practice, Virtual Conference Nov 2021
  3. Condensing Sparse Layers
    Golubeva, Anna, Lasby, Mike,  Ioannou, Yani, and Nica, Mihai
    In 2nd Workshop on Sparsity in Neural Networks, Virtual Jul 2022
  4. ICML
    Monitoring Shortcut Learning using Mutual Information
    Adnan, Mohammed,  Ioannou, Yani, Tsai, Chuan-Yung, Galloway, Angus, Tizhoosh, H. R., and Taylor, Graham W.
    In ICML 2022 Workshop on Spurious Correlations, Invariance, and Stability, Baltimore, MD, USA Jul 2022