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
| Apr 1, 2024 | CML was awarded 24 RGU (approx. 6 A100-years) of GPU compute in the Digital Research Alliance of Canada Resources for Research Groups (RRG) 2024 competition, to support our research. The RRG program provides access to a large-scale GPU clusters for academic research groups in Canada. |
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| Mar 1, 2024 | Muhammad Athar Ganaie was awarded a Mitacs Globalink Graduate Fellowship, to support his MSc research at the University of Calgary. The fellowship will support his research on the development of sparse neural networks for deep reinforcment learning. |
| Jan 16, 2024 | Mike Lasby’s collaborative work with researchers at Google, MIT and the Vector Institute, “Dynamic Sparse Training with Structured Sparsity” (Lasby et al., 2024), was accepted at ICLR 2024! DST methods learn state-of-the-art sparse masks, but accelerating DNNs with unstructured masks is difficult. SRigL learns structured masks, improving real-world CPU/GPU timings! |
| Dec 6, 2023 | Mike Lasby and Adnan Mohammed were awarded highly competitive scholarships in the 2023 Graduate Award Competition: Mike was awarded an Alberta Innovates Graduate Studentship (Technology) in the 2023 Graduate Award Competition. The Government of Alberta funds Alberta Innovates Graduate Studentships (Technology) to support top-quality, research related to Information and Communications Technology (ICT), Nanotechnology, and other technology areas. Adnan was awarded the Alberta Graduate Excellence Scholarship (AGES), recognizing outstanding academic achievement in graduate studies. |
| Nov 30, 2023 | Tejas Pote had his workshop paper Classification Bias on a Data Diet (Pote et al., 2024) accepted at the Conference on Parsimony and Learning (CPAL)’s Recent Spotlight Track, and will present it in Hong Kong in January 2024. |
| May 5, 2023 | Yani Ioannou gave an invited talk at the ICLR 2023 Workshop on Sparsity in Neural Networks in Kigali, Rwanda recently, talking about Mike Lasby’s recent work on learning structured sparsity in dynamic sparse training methods. Yani also participated in the first panel discussion on sparsity. You can watch the full workshop here. |