15-496/782: Artificial Neural Networks
Dave Touretzky

Spring 2004 - Course Syllabus

Last modified: Sun May 2 23:18:10 EDT 2004

Monday, Jan. 12. Organizational meeting; introduction to neural nets. [ps, pdf]

Wednesday, Jan. 14. Perceptrons and the LMS Algorithm. [ps, pdf]

Problem set 1: learning with linear units.

Monday, Jan. 19. No class. Martin Luther King's birthday.

Wednesday, Jan. 21. Pattern Recognition I. [ps, pdf]

Problem set 1 due.

Monday, Jan. 26. Pattern Recognition II. [ps, pdf]

Wednesday, Jan. 28. Backpropagation Learning. [ps, pdf]

Problem set 2: backpropagation learning.

Monday, Feb. 2. Visually-Guided Robot Control. [ps, pdf]

Wednesday, Feb. 4. Optimization Techniques. [Kornel Laskowski] [ps, pdf]

Problem set 2 due.
Problem set 3: ALVINN.

Monday, Feb. 9. Overfitting and Early Stopping. [ps, pdf]

Wednesday, Feb. 11. Recurrent Backprop Networks.

Monday, Feb. 16. No class (President's Day).

Wednesday, Feb. 18. Neural Networks for Control. [ps, pdf]

Problem set 3 due.

Monday, Feb. 23. Shared-Weight Networks.

Wednesday, Feb. 25. Time Series Prediction. [Kornel Laskowski] [ps, pdf]

Monday, March 1. Midterm Exam.

Wednesday, March 3. Radial Basis Functions. [ps, pdf]

Monday, March 8. Spring break. No class.

Wednesday, March 10. Spring break. No class.

Monday, March 15. Object Recognition with Radial Basis Functions. [ps, pdf]

Wednesday, March 17. Competitive Learning and Kohonen Nets. [ps, pdf]

Problem set 4: learning with a distal teacher.

Monday, March 22. The EM (Expectation-Maximization) Algorithm. [ps, pdf]

Wednesday, March 24. Hebbian Learning and Principal Components Analysis. [Kornel Laskowski] [ps, pdf]

Monday, March 29. Hopfield Nets and Boltzmann Machines. [ps, pdf]

Problem set 4 due.

Wednesday, March 31. Boltzmann Machines and Mean Field Approximation

Monday, April 5. Helmholtz Machines; Minimum Description Length.

Wednesday, April 7. Bayesian Networks. [ps, pdf]

Monday, April 12. Computational Learning Theory. [ps, pdf]

Problem set 5: Hopfield and Boltzmann networks.

Wednesday, April 14. Recursive Structures 1: Backprop.

Monday, April 19. Recursive Structures 2: Convolutional Approaches. [ps, pdf]

Problem set 5 due.
Problem set 6: digit recognition.

Wednesday, April 21. Attractor Bump Models.

Monday, April 26. Neurophysiology for Computer Scientists.

Wednesday, April 28. The Mammalian Visual System.

Problem set 6 due.

Monday, May 3. Open book/open notes Final Exam.

1:00 pm to 4:00 pm in Wean Hall 7500.

Dave Touretzky