Lecturer 2x
Category: Academics; Vendor: UNIVERSITY OF CAPE TOWN (UCT).
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This is a response to Thinking About Filtered Evidence Is (Very!) Hard that I thought deserved to be its own post. …
In 1969, Marvin Minsky and Seymour Papert published Perceptrons: An Introduction to Computational Geometry. In it, they showed that a single-layer perceptron cannot compute the XOR function. The main argument relies on linear separability: Perceptrons are linear classifiers, which essentially means drawing a line to separate input that would result in 1 versus 0. You can do it in the OR and AND case, but not XOR. Of course, we’re way past that now, neural networks with one hidden layer can solve that problem.
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MIT Professor Guy Bresler studies computational complexity and researches techniques to learn models from data. A theoretician, he works at the interface of computer science, statistics, probability, and information theory.