14 citations · 20 across the 4 of their papers we have counts for
4 papers
Automatic Neural Network Hyperparameter Optimization for Extrapolation: Lessons Learned from Visible and Near-Infrared Spectroscopy of Mango Fruit
Matthew Dirks, David Poole
Neural networks are configured by choosing an architecture and hyperparameter values; doing so often involves expert intuition and hand-tuning to find a configuration that extrapol…
Auto-Encoder Neural Network Incorporating X-Ray Fluorescence Fundamental Parameters with Machine Learning
Matthew Dirks, David Poole
We consider energy-dispersive X-ray Fluorescence (EDXRF) applications where the fundamental parameters method is impractical such as when instrument parameters are unavailable. For…
Binarised Regression with Instance-Varying Costs: Evaluation using Impact Curves
Matthew Dirks, David Poole
Many evaluation methods exist, each for a particular prediction task, and there are a number of prediction tasks commonly performed including classification and regression. In bina…
Comparing Aggregators for Relational Probabilistic Models
Seyed Mehran Kazemi, Bahare Fatemi, Alexandra Kim +5
Relational probabilistic models have the challenge of aggregation, where one variable depends on a population of other variables. Consider the problem of predicting gender from mov…