A Function Space View of Overparameterized Neural Networks - Rebecca Willet, University of Chicago

A Function Space View of Overparameterized Neural Networks - Rebecca Willet, University of Chicago

Alan Turing Institute via YouTube Direct link

Radon Transform as Line Detector

12 of 17

12 of 17

Radon Transform as Line Detector

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Classroom Contents

A Function Space View of Overparameterized Neural Networks - Rebecca Willet, University of Chicago

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  1. 1 Intro
  2. 2 Overparameterized models in machine learning
  3. 3 An experiment
  4. 4 Training overparameterized neural nets
  5. 5 Approximation theory perspective
  6. 6 Infinite-width two-layer ReLU nets
  7. 7 Learning with norm-controlled infinite-width ReLU networks
  8. 8 From Two-layer ReLU Nets to Convex Nets
  9. 9 Intuition in 1D
  10. 10 Intuition in Higher Dimensions
  11. 11 The Radon Transform in 2D
  12. 12 Radon Transform as Line Detector
  13. 13 Key Derivation
  14. 14 Example
  15. 15 Implications: Comparison to Kernel Learning
  16. 16 Implications: Depth Separation Result
  17. 17 Open Questions

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