77 citations · 111 across the 14 of their papers we have counts for
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cs.LG2020
Efficient Hyperparameter Tuning with Dynamic Accuracy Derivative-Free Optimization
Matthias J. Ehrhardt, Lindon Roberts
Many machine learning solutions are framed as optimization problems which rely on good hyperparameters. Algorithms for tuning these hyperparameters usually assume access to exact s…
math.OC2020★ 2 cited
Scalable Derivative-Free Optimization for Nonlinear Least-Squares Problems
Coralia Cartis, Tyler Ferguson, Lindon Roberts
Derivative-free - or zeroth-order - optimization (DFO) has gained recent attention for its ability to solve problems in a variety of application areas, including machine learning,…
math.OC2020
Inexact Derivative-Free Optimization for Bilevel Learning
Matthias J. Ehrhardt, Lindon Roberts
Variational regularization techniques are dominant in the field of mathematical imaging. A drawback of these techniques is that they are dependent on a number of parameters which h…