ECE 595: Lecture Slides

Professor Stanley H. Chan
Spring 2019

Lecture

Lectures are scheduled every TuTh 4:30-5:45pm at WALC 1055

Lecture 00 (PDF) Handout 00 (PDF) 2019-01-08 Course overview
Lecture 01 (PDF) Handout 01 (PDF) 2019-01-10 Background 1: Linera algebra
Lecture 02 (PDF) Handout 02 (PDF) 2019-01-15 Background 2: Probability (Part 1)
Lecture 03 (PDF) Handout 03 (PDF) 2019-01-17 Background 3: Probability (Part 2) and Optimization (Part 1)
Lecture 04 (PDF) Handout 04 (PDF) 2019-01-22 Background 4: Optimization (Part 2)
Lecture 05 (PDF) Handout 05 (PDF) 2019-01-24 Linear Discriminant Analysis; Separating Hyperplane
Lecture 06 (PDF) Handout 06 (PDF) 2019-01-29 Bayesian Decision Rule 1: Multi-dimensional Gaussian
Lecture 07 (PDF) Handout 07 (PDF) 2019-01-31 Bayesian Decision Rule 2: Optimality of Bayesian, Maximum-likelihood
Lecture 08 (PDF) Handout 08 (PDF) 2019-02-05 Bayesian Decision Rule 3: Maximum-a-Posteriori
Lecture 09 (PDF) Handout 09 (PDF) 2019-02-07 Linear Regression 1
Lecture 10 (PDF) Handout 10 (PDF) 2019-02-12 Linear Regression 2 and Logistic Regression 1
Lecture 11 (PDF) Handout 11 (PDF) 2019-02-14 Logistic Regression 2
Lecture 12 (PDF) Handout 12 (PDF) 2019-02-19 Perceptron Algorithm 1
Lecture 13 (PDF) Handout 13 (PDF) 2019-02-21 Perceptron Algorithm 2
Lecture 14 (PDF) Handout 14 (PDF) 2019-02-26 Support Vector Machine 1
Lecture 15 (PDF) Handout 15 (PDF) 2019-02-27 Support Vector Machine 2
Lecture 16 (PDF) Handout 16 (PDF) 2019-03-05 Support Vector Machine 3
Lecture 17 (PDF) Handout 17 (PDF) 2019-03-19 Adversarial Attack 1
Lecture 18 (PDF) Handout 18 (PDF) 2019-03-21 Adversarial Attack 2
Lecture 19 (PDF) Handout 19 (PDF) 2019-03-26 Adversarial Attack 3
Lecture 20 (PDF) Handout 20 (PDF) 2019-03-28 Is Learning Feasible?
Lecture 21 (PDF) Handout 21 (PDF) 2019-04-02 Probably Approximately Correct
Lecture 22 (PDF) Handout 22 (PDF) 2019-04-04 Growth Function
Lecture 23 (PDF) Handout 23 (PDF) 2019-04-09 VC Dimension
Lecture 24 (PDF) Handout 24 (PDF) 2019-04-16 Bias and Variance
Lecture 25 (PDF) Handout 25 (PDF) 2019-04-18 Overfitting
Lecture 26 (PDF) Handout 26 (PDF) 2019-04-23 Validation
Lecture 27 (PDF) Handout 27 (PDF) 2019-04-25 Course Conclusion

Distinguished Guest Lecture 2019-04-11 Prof. Michael Jordan (UC Berkeley)

Tutorial

Tutorials are schedule every Wednesday 6-7pm at EE 222

Tutorial 01 (PDF) 2019-01-09 Introduction to Python, by Xiangyu. See also Installing Python (PDF)
Tutorial 02 (PDF) 2019-01-16 Homework 1 Discussion, by Guanzhe
Tutorial 03 (PDF) 2019-01-23 Convex Optimization, by Tolunay
Tutorial 04 (PDF) 2019-01-30 Homework 2 Discussion, by Guanzhe
Tutorial 05 (PDF) 2019-02-06 Bayesian Decision Error, by Tolunay
Tutorial 06 (PDF) 2019-02-13 Homework 3 Discussion, by Guanzhe
Tutorial 07 (PDF) 2019-02-19 Regression Methods, by Tolunay
Tutorial 08 (PDF) 2019-02-27 Mid Term Review 1, by Guanzhe
Tutorial 09 (PDF) 2019-03-06 Mid Term Review 2, by Xiangyu
Tutorial 10 (PDF) 2019-03-20 Mid Term Post-review, by Tolunay
Tutorial 11 (PDF) 2019-03-27 Homework 5 Discussion, by Guanzhe Note (PDF)
Tutorial 12 (PDF) 2019-04-03 Homework 5 Q and A, by Xiangyu
Tutorial 13 (PDF) 2019-04-10 Hoeffding inequality, by Tolunay
Tutorial 14 (PDF) 2019-04-17 Homework 6 Discussion, by Guanzhe
Tutorial 15 (PDF) 2019-04-24 Final review, by Guanzhe and Xiangyu