Assignment 2
Probabilistic Models of
Human and Machine Intelligence

CSCI 5822
Spring 2018

Assigned Feb 1
Due Feb 8


The goal of part 1 of this assignment is to give you experience in reading research articles involving probabilistic approaches to machine learning. The goal of part 2 is to let you exercise your math chops dealing with multivariate Gaussians

Part 1

Write brief commentary on the Weiss, Simoncelli, & Adelson (2002) article that we discuss in class on February 1. The commentary should be no more than one page. The article is fairly dense -- both in understanding the issues in human and machine vision as well as in the modeling methodology -- but hopefully the overview of the paper I give in class is sufficient to unpack the paper.

The commentary should start with a summary of what you think the main or most interesting ideas are in the article. You do not need to summarize the entire article.  You can assume that the reader of your commentary will have read the article, but give your take on why others should be interested in it and what research contribution it makes.

 In addition to the summary, include one or more of the following:

Part 2

Consider the multivariate Gaussian distribution x ~ N( μ, Σ), where the vector x has x1 components x1, x2, ... xn. The definition of this distribution is in my notes and in Definition 8.28 of Barber (p. 172). Derive p(x1 | x2, ... xn). Hint: make use of Equation 8.4.19 in Barber (p. 174).
My title