Modeling biological neurons Neural nets are modeled upon real biological neurons, which have the following characteristics: All or none: the input from each entry in the neural net is either O or 1, the output is also 0 or 1…
11. Learning: Identification Trees, Disorder
Identification Trees Problems Non-numeric data Not all characteristics matter Some do matter but not all of the time Cost: certain tests may be more expensive than others Occam’s razor The objective is to build the smallest tree possible (to reduce…
10. Introduction to Learning, Nearest Neighbors
Learning Regularity: “Bulldozer computing” Nearest neighbors: pattern recognition Neural nets: mimic biology Boosting: theory Constraints: human-like learning One-shot Explanation-based learning Nearest neighbor A detection mechanism generates a vector of features. These features are converted in a vector of values that…
9. Constraints: Visual Object Recognition
Borders and faces orientation Discerning borders of objects and face orientation with vectors, an initial computer vision theory seemed plausible but too difficult to implement. Orthographic projection In orthographic projection, the correspondence of a system of points of three known…
8. Constraints: Search, Domain Reduction
https://www.youtube.com/watch?v=d1KyYyLmGpA Domain Reduction Algorithm Vocabulary Variable v: something that can have an assignment Value x: something that can be assigned Domain d: set of all different values Constraint c: limit on variable values With a depth-first search, the domain reduction algorithm…