CS2750: Homework 3

Due: 3/28/2017, 11:59pm

Note: If you are asked to implement something by yourself, it is not ok to use or even look at existing Matlab or Python code, unless it's utility code. If you have questions about what you can use, ask the instructor or the TA.

Part I: Neural Networks (35 points)

In this exercise, you will train and evaluate a very simple neural network. Part II: Convolutional Neural Networks (15 points) -- you don't need to write any code for this, just do it by hand

In this part, you will compute the output from applying a single set of convolution, non-linearity, and pooling operations, on a toy example. Below are your image (with size N = 9) and your filter (with size F = 3).

  1. First, show the output of applying convolution. Use no padding, and a stride of 2 (in both the horizontal and vertical directions).
  2. Second, show the output of applying a Rectified Linear Unit (ReLU) activation.
  3. Third, show the output of applying max pooling over 2x2 regions.
Part III: AdaBoost (35 points)

In this exercise, you will implement the AdaBoost method defined on pages 658-659 in Bishop (Section 14.3). Part IV: Probability Review (15 points)
  1. Bishop Exercise 1.3
  2. Bishop Exercise 1.6
  3. Bishop Exercise 2.8 (first part only) -- Hint: Transform the right-hand side into the left-hand side.