Welcome to video #1 of the Adaptive Experimentation series, presented by graduate student Sterling Baird ‪@sterlingbaird‬ at the 18th IEEE Conference on eScience in Salt Lake City, UT (Oct 1014, 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/sparksbaird/self...

next video in series:    • Traditional sampling techniques (grid...  

0:00 introduction to adaptive experimentation
2:09 Comparing grid/random search with quasirandom 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