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Empirical Results
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Classroom Contents
ADSI Summer Workshop- Algorithmic Foundations of Learning and Control, Pablo Parrilo
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- 1 Intro
- 2 Why do we care
- 3 Optimal transport matrix scaling
- 4 Control entrywise errors
- 5 Three key ideas
- 6 Approximation with polynomials
- 7 Computing a change of expansions
- 8 Plane wave expansion
- 9 Plane wave expansion summary
- 10 Sustainment
- 11 Modern quadratic factor
- 12 Summary
- 13 Harmonic Polynomials
- 14 Product Space of Feature
- 15 Empirical Results
- 16 Methods
- 17 Linear Classification
- 18 Conclusion