Description

This course provides an introduction to pattern recognition and statistical learning. Topics covered include: Bayesian decision theory; parameter estimation; maximum likelihood; the bias-variance trade-off; Bayesian parameter estimation; the predictive distribution; conjugate and non-informative priors; density estimation: parametric vs. kernel-based methods; mixture models; expectation-maximization; applications.

General Information

Lectures
TuTh, 12:30-1:50 PM, CENTR 113
Instructor
Nuno Vasconcelos

Announcements

HW 5
12/02/12 10:48 AM
My apologies for not having changed the deadline for the HW. I only returned last night and did not have time to look into this.
The new deadline is Thursday.

If no one has a problem with this, since the exam is only on the 14, we can give you even some more time. We could move the deadline to Monday the 10th.

In summary, the current deadline is Thursday. If you have a problem with me moving it to the 10 let me know until the next lecture. If I don't hear from anyone, the deadline will be moved to next Monday.
#homework
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Solutions of HW3 has been added to class homepage under Resources
11/15/12 9:45 PM
The teaching staff has posted a new homework_solutions resource.

Title: soln3_q1to3.pdf


You can view it on the course page: https://piazza.com/ucsd/fall2012/ece271a/resources

#class-resources #homework
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Homework one solutions
10/16/12 2:09 PM
Attached please find solutions for homework one.
#homework1
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Staff Office Hours
NameOffice Hours
Mohammad Saberian
When?
Where?
Mandar
When?
Where?
Nuno Vasconcelos
When?
Where?
Weixin Li
When?
Where?

General Resources