Traditional sampling techniques (grid vs random vs sobol vs latin hypercube)

Welcome to video #1 of the Adaptive Experimentation series, presented by graduate student Sterling Baird ‪@sterling-baird‬ at the 18th IEEE Conference on eScience in Salt Lake City, UT (Oct 10-14, 2022). In this video, Sterling introduces the concept of adaptive experimentation and covers traditional sampling approaches, including grid, random, Latin hypercube, and Sobol sampling. He also discusses the use of discrepancy as a metric for performance evaluation. Don't miss the next installment in this informative series on experimental optimization.

Github link to jupyter notebook https://github.com/sparks-baird/self-...

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0:00 introduction to adaptive experimentation
2:09 Comparing grid/random search with quasi-random search with adaptive experimentation approaches (grid vs human intuition)
4:40 traditional optimization jupyter notebook tutorial
6:14 grid sampling
7:45 latin hypercube and sobol sampling
9:36 comparing different sampling
11:05 discrepancy comparison in low and high dimensional data