How Much Data Is Sufficient to Learn High-Performing Algorithms?

How Much Data Is Sufficient to Learn High-Performing Algorithms?

Institute for Pure & Applied Mathematics (IPAM) via YouTube Direct link

Sequence alignment algorithms

3 of 17

3 of 17

Sequence alignment algorithms

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How Much Data Is Sufficient to Learn High-Performing Algorithms?

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  1. 1 Intro
  2. 2 Data-driven algorithm design
  3. 3 Sequence alignment algorithms
  4. 4 Automated configuration
  5. 5 This talk: Main result
  6. 6 Domains with piecewise structure
  7. 7 Primary challenge in combinatorial domains
  8. 8 Example: Sequence alignment
  9. 9 Algorithmic performance
  10. 10 Generalization bounds
  11. 11 Piecewise constant utility function
  12. 12 Primal & dual classes
  13. 13 Warmup: 1-dimensional parameters
  14. 14 Intrinsic complexity
  15. 15 Main result (informal)
  16. 16 Outline
  17. 17 Piecewise constant dual functions

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