Instructor: ChoJui Hsieh Office location: Mathematical Sciences Building (MSB) 4232 Email: chohsieh@ucdavis.edu Office hours: Tues 1:30pm2:30pm and by appointment 
TA: Carlos Colman Meixner Email: cecolmanmeixner@ucdavis.edu 
I. Supvervised learning: regression and classification
II. Optimization for Largescale Machine Learning
 Linear regression
 Support Vector Machines
 Logistic regression
 Kernel methods
 Multiclass/Multilabel
III. Other Popular ML Problems
 Gradient descent
 Stochastic gradient descent
 Coordinate descent
 Duality
 Parallel Optimization Algorithms
 Matrix Completion
 Semisupervised Learning
 Ranking
 Neural Networks
Date 
Topic 
Readings and links 
Lectures 
Assignments 
Thurs 9/24

Course intro 

lecture1_slides 

Tues 9/29 
Linear regression

lecture2_slides 

Thurs 10/1 
Intro to Optimization

Numerical Optimization (by Nocedal and Wright), section 13 
lecture3_slides 

Tues 10/6 
Parallel Optimization

lecture4_slides 

Thurs 10/8 
Support Vector Machines

lecture5_slides 

Tues 10/13 
Optimization Solvers for Support Vector Machines

Pegasos: Primal Estimated subGrAdient SOlver for SVM A dual coordinate descent method for largescale linear SVM 
lecture6_slides 

Thurs 10/15 
Matrix Completion

Maftrix factorization techniques for recommender systems 
lecture7_slides 

Tues 10/20 
Matrix Completion


lecture8_slides complexity 

Tues 10/27 
Multiclass and multilabel learning


lecture9_slides 

Tues 11/3 
Graph Algorithms


lecture10_slides 

Thurs 11/5 
Midterm Exam

lectures 2, 3, 5, 6


Thurs 11/12 
Ranking


lecture11_slides 