Also note that by departmental policy, this course is open only to graduate students (5th year masters are allowed).

Date | Topic | References/Remarks |

PART I: DEPTH | ||

Aug 28 | Logistics and introduction to introduction to ML | SB chapter 2 |

Aug 30 | Perceptrons: Hope, hopelessness, and hope again | SB chapter 9 |

Sep 1 | Optimization for ML [Note:This is a regular lecture on Friday to make up for Sep 21] | Notes |

Sep 6 | Support vector machines | SB chapter 15 |

Sep 8 | Recitation: Optimization | |

Sep 11 | Kernel methods 1 | SB chapter 16 |

Sep 13 | Kernel methods 2 | SB chapter 16 |

Sep 15 | Recitation: Tail bounds | |

Sep 18 | Learning theory 1 | SB Chapters 2 - 5 |

Sep 20 | No class [Make up class was on Sep 1] | |

Sep 22 | Recitation: Linear regression, Logistic regression | |

Sep 25 | Learning theory 2 | SB Chapters 2 - 6 |

Sep 27 | Learning theory 3 | SB Chapters 2 - 6 |

Sep 29 | Recitation: MLE and MAP | |

Oct 2 | Learning theory 4 | SB Chapters 6 - 7 |

Oct 4 | Midterm | All material in previous lectures |

PART II: BREADTH | ||

Oct 9 | Neural networks 1: Introduction. Also, midterm discussion. | SB Chapter 20 |

Oct 11 | Neural networks 2: Representation power | |

Oct 23 | Neural networks 3: Training, automatic differentiation, CNNs, etc. | |

Oct 25 | Theory paper dissection | |

Oct 30 | Model complexity, cross-validation bias-variance tradeoff, interpolation regime, and Neural networks 4 (neural architecture search) | |

Nov 1 | (Large) language models | |

Nov 6 | Unsupervised learning: Clustering, Dimensionality reduction, Diffusion models | SB Chapter 22, 23 |

Nov 8 | Decision trees, random forests, bagging, bootstrapping | SB Chapter 18 |

Nov 13 | Online learning | SB Chapter 21 |

Nov 15 | Semi-supervised learning, Active learning, Multi-armed bandits | Transductive SVM, Active learning, Multi-armed bandits, Ranking via MABs |

Nov 20 | Reinforcement learning 1 | Survey |

Nov 27 | Reinforcement learning 2 and RL from Human Feedback (RLHF) | |

Nov 29 | Applied paper dissection | |

Dec 4 | Graphical models, Causality, Fairness, Interpretability, Alignment | Graphical models, Hiring example, Paper 1, Paper 2 |

Dec 6 | Final exam |