Channel Gating for Cheaper and More Accurate Neural Nets with Babak Ehteshami Bejnordi - #385
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) - Un pódcast de Sam Charrington
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Today we’re joined by Babak Ehteshami Bejnordi, a Research Scientist at Qualcomm. Babak is currently focused on conditional computation, which is the main driver for today’s conversation. We dig into a few papers in great detail including one from this year’s CVPR conference, Conditional Channel Gated Networks for Task-Aware Continual Learning, covering how gates are used to drive efficiency and accuracy, while decreasing model size, how this research manifests into actual products, and more!
