Computer Science 246/446
- Homework 11
- Due Thursday 4/21 in class
- Thrun ch 15, ex 1(a) - 1(d)
- Morris p51 ex 7
- Define a matrix game to be fair if its value is zero. Consider the matrix game [ a 2 ; 1 -1 ].
For which values of the paramter a is the game fair? When does it favor the row player (positive value)?
When does it favor the column player?
- Homework 10
- Due Fri 4/8 5pm
Implement EM to train an HMM for the data from Homework 6. The model should have four hidden states with gaussian observation probabilities. Does the HMM model the data better than the original mixture of gaussians?
- Homework 9
- Due Thursday 3/31 in class
- Bishop 4.12, 4.13, 4.14, 4.15, 4.20
- Homework 8
- Due Tuesday 3/15 in class
- Homework 7
- Due Thursday 3/3 in class
- Kearns and Vazirani 3.1, 3.6
- Homework 6
- Due Fri 2/25 5pm
Implement EM fitting of a mixture of gaussians on the two-dimensional
data set points.dat. You should
try different numbers of mixtures, as well as tied vs. separate
covariance matrices for each gaussian. Which model seems to fit the data best?
- Homework 5
- Due Tu 2/15 in class
- Bishop 6.2, 6.8, 6.9
- Bishop 7.2, 7.7
- Homework 4
- Due Wed 2/9 5pm
- Implement a perceptron and naive bayes on the voting dataset
For perceptron, use a sigmoid activation function and squared error.
For naive bayes, optimize your Dirichlet prior on the tuning set.
Compare results with the decision tree.
- Homework 2
- Due Friday 1/28 5pm
- Implement a decision tree classifier to predict
the party of a US representative from their voting record: voting2.dat.
- Homework 2
- Due Thursday 1/20 in class
- Prove that, given a set of n i.i.d. observations x_1 to x_n, a distribution Q that
minimizes the KL divergence with the empirical distribution P, D(P||Q), also
maximizes the probability of the data Q(x_1 ... x_n).
- Prove (step by step) that entropy for a discrete random variable is maximized by
the uniform distribution.
- Homework 1
- Due Tuesday 1/18 in class
Bishop ex. 1.3, 1.11
gildea @ cs rochester edu
April 14, 2011