Convex Optimization: Fall 2018

Machine Learning 10-725 Instructor: Ryan Tibshirani (ryantibs at cmu dot edu) Important note: please direct emails on all course related matters to the Head TA, not the Instructor. The subject line of all emails should begin with "[10-725]". Head TA: Po-Wei Wang (poweiw at andrew dot cmu dot edu) TAs: Kartik Gupta (kartikg1 at andrew dot cmu dot edu) Biswajit Paria (bparia at andrew dot cmu dot edu) Akash Umakantha (aumakant at andrew dot cmu dot edu) Wayne Zhao (wzhao1 at andrew dot cmu dot edu) Lecture times: Mondays and Wednesdays 1:30-2:50pm, Wean Hall 7500 Office hours: RT: Mondays 12:30-1:30pm, Baker 229B PW: Wednesdays 12:30-1:30pm, Gates 8221 AU: Thursdays 4-5p, Gates 8106 WZ: Fridays 3-4pm, Roberts 245 Syllabus: here. Scribing: sign up, latex template. Discussions: Piazza group.

Schedule

Homework

• Homework 1 [Latex source], due Fri Sept 14
  Data files: baboon.csv, toy.csv
  
  
• Homework 2 [Latex source], due Fri Sept 28
  Data files: X_train.csv, Y_train.csv
  
  
• Homework 3 [Latex source], due Fri Oct 12
  Data files: data.txt
  
  
• Homework 4 [Latex source], due Fri Nov 2
  Data files: data.txt, hwk4_qs3.zip
  
  
• Homework 5 [Latex source], due Fri Nov 30
  Data files:

Project

• Project milestone 1: Proposal, due Mon Oct 1
  2 page write up in NIPS format
  
  
• Project milestone 2: Progress report, due Fri Nov 9
  4-5 page write up in NIPS format
  Submission and reviewing instructions, through the EasyChair system
  
  
• Project final presentations and report
  Presentations at COPTS, Mon Dec 10
  Written report, due Thurs Dec 13
  7-8 page write up in NIPS format

Review aids

• Linear algebra review, videos by Zico Kolter
• Real analysis, calculus, and more linear algebra, videos by Aaditya Ramdas
• Convex optimization prequisites review from Spring 2015 course, by Nicole Rafidi
• See also Appendix A of Boyd and Vandenberghe (2004) for general mathematical review