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.
|Jul 13, 2022||Our workshop paper, (Golubeva et al., 2022), was accepted at the 2nd Sparsity in Neural Networks workshop.|
|Jun 13, 2022||Our workshop paper, (Adnan et al., 2022), was accepted at the ICML 2022 workshop on spurious correlations, invariance and stability.|
|Jan 12, 2022||Our paper, (Evci et al., 2022), has been accepted to be presented as an Oral at the 2022 AAAI Conference! The conference had a 15% acceptance rate for posters alone.|
|Sep 1, 2021||Yani Ioannou started as an Assistant Professor at the University of Calgary.|
- Gradient Flow in Sparse Neural Networks and How Lottery Tickets WinIn Proceedings of the 36th AAAI Conference on Artificial Intelligence, Vancouver, BC, Canada Feb 2022
- Domain-Agnostic Clustering with Self-DistillationIn 2nd NeurIPS Workshop on Self-Supervised Learning: Theory and Practice, Virtual Conference Nov 2021
- Condensing Sparse LayersIn 2nd Workshop on Sparsity in Neural Networks, Virtual Jul 2022
- ICMLMonitoring Shortcut Learning using Mutual InformationIn ICML 2022 Workshop on Spurious Correlations, Invariance, and Stability, Baltimore, MD, USA Jul 2022