DiscoverThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Channel Gating for Cheaper and More Accurate Neural Nets with Babak Ehteshami Bejnordi - #385
Channel Gating for Cheaper and More Accurate Neural Nets with Babak Ehteshami Bejnordi - #385

Channel Gating for Cheaper and More Accurate Neural Nets with Babak Ehteshami Bejnordi - #385

Update: 2020-06-22
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Today we’re joined by Babak Ehteshami Bejnordi, a Research Scientist at Qualcomm.

Babak works closely with former guest Max Welling and 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

We also discuss the paper TimeGate: Conditional Gating of Segments in Long-range Activities, and another paper from this year’s ICLR conference, Batch-Shaping for Learning Conditional Channel Gated Networks. We cover how gates are used to drive efficiency and accuracy, while decreasing model size, how this research manifests into actual products, and more! 

For more information on the episode, visit twimlai.com/talk/385. To follow along with the CVPR 2020 Series, visit twimlai.com/cvpr20

Thanks to Qualcomm for sponsoring today’s episode and the CVPR 2020 Series!

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Channel Gating for Cheaper and More Accurate Neural Nets with Babak Ehteshami Bejnordi - #385

Channel Gating for Cheaper and More Accurate Neural Nets with Babak Ehteshami Bejnordi - #385

Sam Charrington