W/F: 2:20-3:40 PM (480 Dreese Lab)
TA: Chaitanya Kulkarni,
Office hours:
my office hours: Wed/Fri 4:15 - 5:15 pm (DL 589).
TA's office hour: Mon 1-2 pm (BE 406).
Tools from Probability: Concentration Inequalities
The Statistical Learning Framework.
The Vapnik-Chervonenkis (VC) Dimension, Part 1.
Fundamental Theorems of Statistical Learning (The VC Dimension, Part 2).
Linear Classifiers and Perceptron Algorithm.
Weak versus Strong Learning and Boosting.
Intro to a General Learning Model: Linear Regression
Intro to Convex Learning (Definitions).
Basic notions from Convex Analysis.
Convex Lipschitz functions, and Gradient Descent Algorithm.
Learning via Stochastic Gradient Descent.
Regularization and Stability - Part 1.