A Classical Algorithm Framework for Dequantizing Quantum Machine Learning

A Classical Algorithm Framework for Dequantizing Quantum Machine Learning

Simons Institute via YouTube Direct link

Unifying quantum linear algebra

3 of 16

3 of 16

Unifying quantum linear algebra

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A Classical Algorithm Framework for Dequantizing Quantum Machine Learning

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  1. 1 Intro
  2. 2 Dequantizing quantum lipear algebra
  3. 3 Unifying quantum linear algebra
  4. 4 Matrix notation
  5. 5 Input/output assumptions of QML
  6. 6 Powering up classical computation with measurements
  7. 7 Sample and query access
  8. 8 Quantum-inspired sketching, aka importance sampling
  9. 9 Importance sampling can approximate matrix products
  10. 10 All we need are RUR decompositions
  11. 11 Main theorem: even singular value transformation
  12. 12 Proof sketch of main theprem
  13. 13 Interpreting the even SVT result
  14. 14 Comparing quantum-inspired SVT to quantum SVT
  15. 15 Applications
  16. 16 Implications for exponential speedups in QML

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