17 citations · 19 across the 3 of their papers we have counts for
4 papers
Adaptive Weighting Scheme for Automatic Time-Series Data Augmentation
Elizabeth Fons, Paula Dawson, Xiao-jun Zeng +2
Data augmentation methods have been shown to be a fundamental technique to improve generalization in tasks such as image, text and audio classification. Recently, automated augment…
Augmenting transferred representations for stock classification
Elizabeth Fons, Paula Dawson, Xiao-jun Zeng +2
Stock classification is a challenging task due to high levels of noise and volatility of stocks returns. In this paper we show that using transfer learning can help with this task,…
Evaluating data augmentation for financial time series classification
Elizabeth Fons, Paula Dawson, Xiao-jun Zeng +2
Data augmentation methods in combination with deep neural networks have been used extensively in computer vision on classification tasks, achieving great success; however, their us…
A novel dynamic asset allocation system using Feature Saliency Hidden Markov models for smart beta investing
Elizabeth Fons, Paula Dawson, Jeffrey Yau +2
The financial crisis of 2008 generated interest in more transparent, rules-based strategies for portfolio construction, with Smart beta strategies emerging as a trend among institu…