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Schedule
The notes can be found in bCourse files.
| Jan 18 | Introduction | Jan 20 | Markov, Chebyshev, and Chernoff |
| Jan 25 | Sub-Gaussian and sub-Exponential R.V. | Jan 27 | Sub-Exponential, Johnson-Lindenstrauss lemma |
| Feb 1 | Martingale concentration inequalities | Feb 3 | Gaussian concentration inequalities |
| Feb 8 | Further concentration inequalities | Feb 10 | Uniform law of large numbers and Rademacher complexity |
| Feb 15 | Rademacher complexity | Feb 17 | VC dimension, Metric entropy |
| Feb 22 | Chaining method | Feb 24 | Metric entropy method |
| Mar 1 | Rademacher complexity bound | Mar 3 | Random matrices |
| Mar 8 | Concentration of sample covariance I | Mar 10 | |
| Mar 15 | Concentration of sample covariance II | Mar 17 | Sparse linear model I |
| Mar 29 | Sparse linear model II | Apr 1 | Sparse linear model III |
| Apr 5 | Sparse linear model IV | Apr 7 | PCA in high dimension I |
| Apr 12 | PCA in high dimension II | Apr 14 | Non-parametric regression I |
| Apr 19 | Non-parametric regression II | Apr 21 | Non-parametric regression III |
| Apr 25 | Minimax lower bound I | Apr 27 | Minimax lower bound II
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