10 citations · 12 across the 4 of their papers we have counts for
4 papers
Optimizing the optimizer for data driven deep neural networks and physics informed neural networks
John Taylor, Wenyi Wang, Biswajit Bala +1
We investigate the role of the optimizer in determining the quality of the model fit for neural networks with a small to medium number of parameters. We study the performance of Ad…
Exploiting the Power of Levenberg-Marquardt Optimizer with Anomaly Detection in Time Series
Wenyi Wang, John Taylor, Biswajit Bala
The Levenberg-Marquardt (LM) optimization algorithm has been widely used for solving machine learning problems. Literature reviews have shown that the LM can be very powerful and e…
A Distribution Similarity Based Regularizer for Learning Bayesian Networks
Weirui Kong, Wenyi Wang
Probabilistic graphical models compactly represent joint distributions by decomposing them into factors over subsets of random variables. In Bayesian networks, the factors are cond…
Bayesian Optimization Using Monotonicity Information and Its Application in Machine Learning Hyperparameter
Wenyi Wang, William J. Welch
We propose an algorithm for a family of optimization problems where the objective can be decomposed as a sum of functions with monotonicity properties. The motivating problem is op…