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- 2nd Round of scribe assignments.
- Please check what lecture you're assigned to, and let us know if the assignment no longer suits you.
- Also let us know if you would like to volunteer for any of the open lectures.
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Scribe template [LaTeX].
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Lecture 2. Introduction. Risk minimization. [Th 2/8, Douglas Fearing]
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Lecture 3. Convergence. Non-parametric density estimation. [T 2/13, Sleiman Itani]
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Lecture 4. Uniform Convergence. Finite parametrizations. [Th 2/15, Rajiv Menjoge]
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Lecture 5. Annealed entropy. UCEP with indicator funtions. [Th 2/22]
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Lecture 6. Growth function. VC dimension. [T 2/27, Mac Schwager]
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Lecture 7. Exchangeability. De Finetti's theorem. [Th 3/1]
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Lecture 8. Support Vector Machines. Duality. [T 3/6]
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Lecture 9. Convergence properties of SVMs. Extensions. [Th 3/8, Kostas Bimpikis]
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Lecture 10. Coding and compression. [T 3/13, Giorgio Magri]
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Lecture 11. Minimum description length. Model selection. [Th 3/15]
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Lecture 12. Structured risk minimization and MDL. [T 3/20, Wen Dong]
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Lecture 13. System identification. ARX model. Persistance of excitation. [T 3/22, Ilan Lobel]
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Lecture 14. Asymptotic normality. State space models. [T 4/3, Sleiman Itani]
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Lecture 15. HMMs. Forward-Backward and EM algorithms. [Th 4/5, Rajiv Menjoge]
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