This is the course material for CSE 5526: Neural Network at Ohio State University, as taught by Michael Mandel in Fall 2014.

Topics (syllabus)

Date Subject Slides Reading Due
2014/08/28 Introduction & McCulloch-Pitts networks 01a-intro Intro.1-6
2014/09/02 Perceptrons 01b-perceptron 1.1-3, 1.5, 1.7
2014/09/04 Perceptrons 01b-perceptron 1.1-3, 1.5, 1.7
2014/09/09 Regression & Least Mean Square algorithm 02-regression 2.1-5,9; 3.1-5,10-14 hw1
2014/09/11 Regression & Least Mean Square algorithm 02-regression 2.1-5,9; 3.1-5,10-14
2014/09/16 Multilayer perceptrons 03-mlp 4.1-8 hw2
2014/09/18 Multilayer perceptrons 03-mlp 4.1-8
2014/09/23 Multilayer perceptrons 03b-trainTest 4.11-13,17,20
2014/09/25 Multilayer perceptrons 03c-mlpTips 4.11-13,17,20
2014/09/30 Radial basis function networks 04-rbf 2.7; 5.1-4 proj1
2014/10/2 Radial basis function networks 04-rbf 2.7; 5.1-4
2014/10/7 Review so far 04b-review
2014/10/09 In-class practice test midtermPractice proj2
2014/10/14 Midterm midterm
2014/10/16 Support vector machines 05a-svm1 6.1-3
2014/10/21 Support vector machines 05b-svm2 6.4-7,11
2014/10/23 Support vector machines 05c-svmKernels 05d-svmNonsep 6.1-3
2014/10/28 Unsupervised learning & self-organization 06-unsupervised 9.1-5,11 hw3
2014/10/30 In class exercises 06b-inClassProblems
2014/11/04 Hopfield networks 07-hopfieldNet 13.7-8
2014/11/06 Guest lecture by Jihun Hamm on Optimization 07b-optimization
2014/11/11 Veterans day, no class
2014/11/13 Hopfield networks 07-hopfieldNet proj3 (data)
2014/11/18 Stochastic methods & Boltzmann machines 11.1-2,5-7
2014/11/20 Stochastic methods & Boltzmann machines 08-boltzmannMachine 11.1-2,5-7
2014/11/25 Deep networks 09-dbn 11.8 hw4
2014/11/27 Thanksgiving, no class
2014/12/02 Deep networks 09-dbn 11.9
2014/12/04 Catch up, review, current topics 10-review2
2014/12/09 Catch up, review, current topics 10-review2 hw5