Nearest neighbor search is an optimization problem of finding the point in a given set that is closest to a given point. It can be generalized to a k-NN search, where the k closest points are found. The space and dissimilarity function used can vary, but most commonly it is a metric space with a distance metric such as Euclidean or Manhattan distance.

Stanford University

Spring 2022

CS 168 provides a comprehensive introduction to modern algorithm concepts, covering hashing, dimension reduction, programming, gradient descent, and regression. It emphasizes both theoretical understanding and practical application, with each topic complemented by a mini-project. It's suitable for those who have taken CS107 and CS161.

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