Math 4530

Course Description

Office Hours: Monday 11-12  & Tuesday 2:30-3:20  (Math 229)

Lecture 1: Introduction and Motivation

Lecture 2: Basic Concentration Inequalities

Lecture 3: Law of Large Numbers

Lecture 4: Volume of the Unit Ball

Lecture 5: Volume at Equator

Lecture 6: Sampling from the Unit Ball

Lecture 7: Gaussian Annulus Theorem

Lecture 8: Numerical Verification (MATLAB Script)

Lecture 9: Some Applications of the Gaussian Annulus Theorem

Lecture 10: Singular Value Decomposition 

Lecture 11: Singular Value Decomposition II

Lecture 12: Singular Value Decomposition III

Lecture 13-15: Linear Algebra Review

Lecture 16: Singular Value Decomposition IV

Lecture 17: Singular Value Decomposition V (MATLAB Script and Script PDF)

Lecture 18: Clustering Mixtures of Gaussians

Lecture 19: Eigenfaces (Script PDF)

Lecture 20: Compressed Sensing I (type-set notes from a previous course)

Lecture 21: Compressed Sensing II

Lecture 22: Compressed Sensing III

Lecture 23: Compressed Sensing IV

Lecture 24: Introduction to Machine Learning

Lecture 25: Logical Fallacies

Lecture 26: Empirical Risk Minimization

Lecture 27: Introduction to Neural Nets

Lecture 28: Learning in Neural Nets

Lecture 29: Multivariate Calculus review (for backpropagation)

Lecture 30: Backpropagation

Lecture 31: Improving Generalization

Lecture 32: Improving Generalization II

Lecture 33: Bayesian Approach

Lecture 34: Introduction to Streaming and Sketching

Lecture 35: Morris' Algorithm

Homework Assignments: 

1. Assignment 1 (Due Feb. 1st)

2. Assignment 2 (Due Feb. 8th)

3. Assignment 3 (Due Feb. 15th)

4. Assignment 4 (Due Feb. 22nd)

5. Assignment 5 (Due March 1st)

6. Assignment 6 (Due March 8th)

7. Assignment 7 (Due March 15th)

8. Assignment 8 (Due April 12th)

9. Assignment 9 (Due April 19th)

10. Assignment 10 (Due April 26th)