RECENT ADVANCES IN FINDING BEST OPERATING CONDITIONS

By R. Anderson. 1953

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Benchmark and Survey of Automated Machine Learning Frameworks (2019, neutral): “Another widely-known approach is random search (Anderson, 1953).”
Survey on Automated Machine Learning (2019, background): “2 Random Search Another widely-known approach is random search (Anderson, 1953).”
Fundamentals of natural computing: an overview (2007, background): “, [12,40,106,109]), but its most popular version, known as the canonical or standard GA, was presented by J.”
Minimization by Random Search Techniques (1981, methodology): “of Rn, for example C = [-1, 1]".”
Point Estimates of Ordinates of Concave Functions (1954, background): “1 A brief review of these procedures has recently been published by Anderson [1].”
Optimization of Convex Functions with Random Pursuit (2011, unknown): “90C25, 90C56, 68W20, 62L10 1.”
LSTM: A Search Space Odyssey (2015, methodology): “Random search (Anderson, 1953; Solis & Wets, 1981; Bergstra & Bengio, 2012) is used to ﬁnd the best performing hyperparameters for each variant on each problem, enabling a reliable comparison of the performance of different variants.”