Introduction to Neural Networks

Readings

Lec #	Topics	READINGS
1	From Spikes to Rates	Koch, Christof. Biophysics of Computation: Information Processing in Single Neurons. New York, NY: Oxford University Press, 2004, section 14.2, pp. 335-341. ISBN: 9780195181999. Ermentrout, Bard. “Reduction of Conductance-Based Models with Slow Synapses to Neural Nets.” Neural Computation 6, no. 4 (July 1994): 679-695.
2	Perceptrons: Simple and Multilayer
3	Perceptrons as Models of Vision	Marr, David. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. New York, NY: W.H. Freeman & Company, 1983, section 2.2, pp. 54-79. ISBN: 9780716715672. Hubel, David H. Eye, Brain, and Vision. New York, NY: W.H. Freeman & Company, 1988, chapter 3, pp. 39-46. ISBN: 9780716750208. LeNet Web site
4	Linear Networks
5	Retina	Adelson, E. H. “Lightness Perception and Lightness Illusions.” The New Cognitive Neurosciences. Edited by Michael S. Gazzaniga. 2nd ed. Cambridge, MA: MIT Press, 1999, pp. 339-351. ISBN: 9780262071956. Hartline, H. K., and F. Ratliff. “Inhibitory Interaction in the Retina of Limulus.” Physiology of Photoreceptor Organs. Edited by Michelangelo G. F. Fuortes. New York, NY: Springer-Verlag, 1972, pp. 382-447. ISBN: 9780387057439.
6	Lateral Inhibition and Feature Selectivity	Press, William H., Saul A. Teukolsky, William T. Vetterling, and Brian P. Flannery. Numerical Recipes in C: The Art of Scientific Computing_._ New York, NY: Cambridge University Press, 1992, chapters 12, and 13. ISBN: 9780521431088. Strang, Gilbert. Introduction to Applied Mathematics. Wellesley, MA: Wellesley-Cambridge Press, 1986, section 4.2, pp. 290-309. ISBN: 9780961408800.
7	Objectives and Optimization
8	Hybrid Analog-Digital Computation Ring Network	Hahnloser, R. H., R. Sarpeshkar, M. A. Mahowald, R. J. Douglas, and H. S. Seung. “Digital selection and analog amplification coexist in a cortex-inspired silicon circuit.” Nature 405, no. 6789 (June 22, 2000): 947-51. Hahnloser, Richard H., H. Sebastian Seung, and Jean-Jacques Slotine. “Permitted and Forbidden Sets in Symmetric Threshold-Linear Networks.” Neural Computation 15, no. 3 (March 2003): 621-38.
9	Constraint Satisfaction Stereopsis
10	Bidirectional Perception
11	Signal Reconstruction
12	Hamiltonian Dynamics
	Midterm
13	Antisymmetric Networks
14	Excitatory-Inhibitory Networks Learning
15	Associative Memory
16	Models of Delay Activity Integrators
17	Multistability Clustering
18	VQ PCA
19	More PCA Delta Rule
20	Conditioning Backpropagation
21	More Backpropagation
22	Stochastic Gradient Descent
23	Reinforcement Learning
24	More Reinforcement Learning
25	Final Review