Office hours: Tuesday 1245-145 PM
Piazza webpage
Syllabus
Syllabus
Announcements
| Aug 19 | Homework 1 is up (due before class Tuesday, Sept 3) | HW1 file1 file2 file3 |
| Sept 3 | Homework 2 is up (due before class, Tuesday, Sept 17) | HW2 |
| Sept 17 | Dates for Midterm 1: Oct 10, and Midterm 2 on Nov 21 | |
| Sept 17 | Homework 3 is up (due before class on Tuesday, Oct 1) | HW3 |
| Oct 2 | Homework 4 is up (due before midnight, Sunday, Oct 20) | HW4 |
| Oct 23 | Homework 5 is up (due before class, Thursday, Nov 7) | HW5 |
| Oct 29 | Code for MCMC demo 2 | R shiny file |
| Nov 10 | Earlier midterms | 2016 2017 2018 |
| Nov 8 | Homework 6 is up (due before midnight Sunday, Nov 25) | HW6, message |
| Dec 11 | Midterms 1 and 2 | Midterm 1 Midterm 2 |
Reading
| Week 1 |
R Markdown: Tutorial 1 ,
Tutorial 2 (we will use this for the homeworks) Iain Murray's cribsheet, Sam Roweis' notes, A short introduction to R , Plotting with ggplot2 Useful references: Review of probability and statistics (Stanford notes) , R Manual |
| Week 1 (contd.) |
R crash course:
Crash course in R Earlier midterms: 2018. 2017, 2016, |
| Week 2 |
Some notes on gradient descent here .
This is also useful. Section 5 on eigenvalues of Richard Shewchuk's tutorial on the conjugate gradient method |
| Week 3 | Complexity and big-O notation: Link 1 ,
Link 2
Link 3 This is a nice introduction to big-O notation Quicksort Knapsack problem (ignore the C code) The Needleman-Wunsch algorithm |
| Week 4 | Clustering: Read Section 10.3 of An Introduction to Statistical Learning MLE for the multivariate Gaussian. See Sections 2 and 3 here . Jensen's inequality here . Kullback-Liebler divergence (Sections 1 to 8 here ). |
Week 5 |
Tony Jebara's' introduction to exponential family distributions. Jeff Bilmes' tutorial on the EM algorithm. If you're feeling ambitious, here is the original paper on the EM algorithm. Some project ideas here , I'll try to add to this. You can search for others on other course webpages. In general, make sure your project allows you to code up some non-trivial algorithm (rather than just use packages) |
Week 6 |
The Baum-Welch algorithm here . Solution to an EM problem from 2015 here . Part of solution to EM problem from 2016 here . Solution to an EM problem from 2017 here . |
| Week 7 |
Some notes on gradient descent here .
This is also useful. Section 5 on eigenvalues of Richard Shewchuk's tutorial on the conjugate gradient method |
Week 9 | Some notes on rejection sampling here . Some additional notes on importance sampling here and here . |
| Week 10 |
Jeff Gills's introduction to MCMC. Andrieu et al.'s introduction to MCMC. Radford Neal, in rather more detail on MCMC. |