Calgary ML Lab @UCalgaryML
University of Calgary Machine Learning Lab calgaryml.com Calgary, AB Joined June 2021-
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@UCalgaryML will be at #ICML2025 in Vancouver🇨🇦 next week: our lab has 6 different works being presented by 5 students across both the main conference & 6 workshops! We are also recruiting fully-funded ML PhD/MSc students🧑🎓If attending, reach out to me on Whova app to meet 📅
1/10 🧵 🔍Can weight symmetry provide insights into sparse training and the Lottery Ticket Hypothesis? 🧐We dive deep into this question in our latest paper, "Sparse Training from Random Initialization: Aligning Lottery Ticket Masks using Weight Symmetry", accepted at #ICML2025
I'm proud that the @UCalgaryML lab will have 6 different works being presented by 6 students across #NeurIPS2024, in workshops (@unireps, @WiMLworkshop, MusiML) and the main conference! 🎉 Hope to see you at our posters/talks 🤓, full schedule at calgaryml.com 🧵(1/4)
For more details, check out our full paper … 👇🏼 🔗: neurips.cc/virtual/2024/1… Joint work w/ @adnan_ahmad1306, @EkanshSh, and @yanii from @VectorInst and @UCalgary. Visit our poster session on Dec 14 at #NeurIPS2024! 👋🏻 Supported by: @UCalgaryML (6/6)
Really excited to be presenting this work from my lab at the @NeurIPSConf 2024 @unireps workshop! 🎉 If you are at NeurIPS and interested in the Lottery Ticket Hypothesis/sparse training, don’t miss our poster on Sat Dec 14th, 3:45-5:00 PM 🖼️🤓 @UCalgaryML @VectorInst
Really excited to be presenting this work from my lab at the @NeurIPSConf 2024 @unireps workshop! 🎉 If you are at NeurIPS and interested in the Lottery Ticket Hypothesis/sparse training, don’t miss our poster on Sat Dec 14th, 3:45-5:00 PM 🖼️🤓 @UCalgaryML @VectorInst
Congratulations @adnan_ahmad1306 on receiving the @RBCBorealis Fellowship! Adnan is a PhD student in the @UCalgaryML lab at @SchulichENGG/@UCalgary, and @VectorInst, co-supervised by @rahulgk.
Congratulations @adnan_ahmad1306 on receiving the @RBCBorealis Fellowship! Adnan is a PhD student in the @UCalgaryML lab at @SchulichENGG/@UCalgary, and @VectorInst, co-supervised by @rahulgk.
Happy to share our work on Knowledge Distillation temperature🌡️ and fairness⚖️. Must-read for AI practitioners given the prevalence of distilled models! KD is crucial in deploying AI, e.g. limited hardware, real-time applications 🙏@sarahookr @mikelasby for feedback! @UCalgaryML
Happy to share our work on Knowledge Distillation temperature🌡️ and fairness⚖️. Must-read for AI practitioners given the prevalence of distilled models! KD is crucial in deploying AI, e.g. limited hardware, real-time applications 🙏@sarahookr @mikelasby for feedback! @UCalgaryML
"Dynamic Sparse Training with Structured Sparsity" (openreview.net/forum?id=kOBkx…) 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
I’m excited to share that I’ve received an Amazon Research Award for my proposal "Addressing Catastrophic Forgetting with Dynamic Sparse Training" at @UCalgaryML/@UCalgary! Learn more about the program on the @AmazonScience website: amzn.to/ara-fall-winte… #AmazonResearchAwards
I was happy to recently be informed my 2022 DG proposal was also awarded a @NSERC_CRSNG and @NationalDefence DND Discovery Grant Supplement — one of only 20 awarded nationally — to further support and accelerate research at @UCalgaryML! #DiscoveryGrants #NSERCsupport #CdnSci
Key takeaways: - Initialization is important for older NNs: use sparsity aware init. - For modern NNs, init doesn't matter: improving gradient flow during training helps (i.e. RigL) - Lottery tickets work since they re-locate the pruning solutions.
Key takeaways: - Initialization is important for older NNs: use sparsity aware init. - For modern NNs, init doesn't matter: improving gradient flow during training helps (i.e. RigL) - Lottery tickets work since they re-locate the pruning solutions.
Work recently published by our close collaborators Drs. @marianapbento and @richardfrayneca! Deep Learning in Large and Multi-Site Structural Brain MR Imaging Datasets frontiersin.org/article/10.338…
Join us for our #AAAI2022 *Oral Presentation* of our paper on Sparse DNN training: "Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win" tomorrow (Feb 24) @ 10:30-11:45am PST! Poster at 8:45-10:30am/Feb 27 4:45-6:30pm. Work with @utkuevci, @ynd, @cem_keskin_.

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