Deep Learning

Deep Learning Indaba Practicals 2022
A collection of high-quality practicals covering a variety of modern machine learning techniques.
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Deep Learning Indaba Practicals 2022
Just-in-Time Sparsity: Learning Dynamic Sparsity Schedules
Sparse neural networks have various benefits such as better efficiency and faster training and inference times, while maintaining the …
Kale-ab Tessera, Chiratidzo Matowe, Arnu Pretorius, Benjamin Rosman, Sara Hooker
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Just-in-Time Sparsity: Learning Dynamic Sparsity Schedules
Keep the Gradients Flowing: Using Gradient Flow to Study Sparse Network Optimization
We use gradient flow to study sparse network optimization.
Kale-ab Tessera, Sara Hooker, Benjamin Rosman
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Keep the Gradients Flowing: Using Gradient Flow to Study Sparse Network Optimization
On Sparsity In Deep Learning: The Benefits And Pitfalls Of Sparse Neural Networks And How To Learn Their Architectures
Overparameterization in deep learning has led to many breakthroughs in the field. However, overparameterized models also have …
Kale-ab Tessera
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