74 citations · 109 across the 3 of their papers we have counts for
3 papers
cs.AI2016★ 74 cited
Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates
Ilija Ilievski, Taimoor Akhtar, Jiashi Feng +1
Automatically searching for optimal hyperparameter configurations is of crucial importance for applying deep learning algorithms in practice. Recently, Bayesian optimization has be…
stat.ML2014★ 34 cited
A General Stochastic Algorithmic Framework for Minimizing Expensive Black Box Objective Functions Based on Surrogate Models and Sensitivity Analysis
Yilun Wang, Christine A. Shoemaker
We are focusing on bound constrained global optimization problems, whose objective functions are computationally expensive black-box functions and have multiple local minima. The r…
stat.ML2014★ 1 cited
Sensitivity Analysis for Computationally Expensive Models using Optimization and Objective-oriented Surrogate Approximations
Yilun Wang, Christine A. Shoemaker
In this paper, we focus on developing efficient sensitivity analysis methods for a computationally expensive objective function in the case that the minimization of it has j…