Schedule

  • Class: Tu, Th 9:30 - 10:45, Room 160-323
  • Office Hours: Tu 11:00 - 12:30

Lecture Notes

  1. Introduction (ps, pdf, 2ps, 2pdf)
  2. Probability on finite sets (ps, pdf, 2ps, 2pdf)
  3. Random variables (ps, pdf, 2ps, 2pdf)
  4. Estimation and prediction (ps, pdf, 2ps, 2pdf)
  5. Random vectors (ps, pdf, 2ps, 2pdf)
  6. Classification (ps, pdf, 2ps, 2pdf)
  7. Continuous random variables (ps, pdf, 2ps, 2pdf)
  8. Continuous random vectors (ps, pdf, 2ps, 2pdf)
  9. Conditional density (ps, pdf, 2ps, 2pdf)
  10. MMSE estimation (ps, pdf, 2ps, 2pdf)
  11. The linear model (ps, pdf, 2ps, 2pdf)
  12. Recursive estimation (ps, pdf, 2ps, 2pdf)
  13. The Kalman filter (ps, pdf, 2ps, 2pdf)
  14. Gaussian stochastic processes (ps, pdf, 2ps, 2pdf)
  15. Estimating moments (ps, pdf, 2ps, 2pdf)
  16. Regression and learning (ps, pdf, 2ps, 2pdf)
  17. Bias and variance (ps, pdf, 2ps, 2pdf)

Additional notes

  • Matrix facts and completion of squares (ps, pdf, 2ps, 2pdf)

Homework

  • Homework 1 (pdf)
  • Homework 1 sol (pdf)
  • Homework 2 (pdf)
  • Homework 2 sol (pdf)
  • Homework 3 (pdf)
  • Homework 3 sol (pdf)
  • Midterm 2011 (pdf)
  • Midterm 2011 sol (pdf)
  • Midterm 2013 (pdf)
  • Midterm 2013 sol (pdf)
  • Homework 4 (pdf)
  • Homework 4 sol (pdf)
  • Homework 5 (pdf)
  • Homework 5 (pdf)
  • Homework 6 (pdf)
  • Final 2011 (pdf)
  • Final 2011 (pdf)

Prerequisites

  • The prerequisite for this course is EE263. You should also have prior exposure to basic probability.

Homework

  • Homeworks will go out on Thursday at 5pm, and will be due at 5pm the following Thursday. Homeworks must be scanned and emailed to me.

Exams

  • The midterm and final exam will be 24hr take home. For the midterm, you can receive it by email anytime between 5pm on Feb 12 to 5pm on Feb 14. You should email the scanned exam to me 24 hours later.

Calendar

  • Tu 1/7. First class
  • Th 3/14. Last class
  • 2/12 to 2/14. Mid-term
  • 3/14 to 3/22. Final Exam