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Regime-switching advantage in statistical arbitrage strategies conditioned on time series momentum and volatility in leveraged exchange traded funds : theory and evidence
(University of Wisconsin--Whitewater, 2019-09)
The phenomena of volatility decay (also known as time decay) and path dependence in leveraged exchange traded funds (ETF) markets have been documented in the literature. This dissertation examined whether it is possible ...
Emergent behavior in neuroevolved agents
(University of Wisconsin--Whitewater, 2018-11)
Neural networks have been widely used for their ability to create generalized rulesets for a given set of training data. In applications where no such training data exists such as new video games, they are often overlooked ...
Superresolution recurrent convolutional neural networks for learning with multi-resolution whole slide images
(University of Wisconsin--Whitewater, 2018-11)
A recurrent convolutional neural network is supervised machine learning way to process images that has both properties of convolutional and recurrent networks. We propose Convolutional Neural Network (CNN) based approach ...
A residual recurrent convolutional neural network for image superresolution with whole slide images
(University of Wisconsin--Whitewater, 2019-04)
Presented is a deep learning based computational approach to solve the problem of enhancing the resolution of images gained from commonly available low magnification scanners, also known as the image super-resolution (SR) ...
Modeling user behavior to construct counter strategies
(University of Wisconsin--Whitewater, 2019-08)
We are working on the development of an adaptive learning framework addressing covariate shift, experienced in Behavioral Cloning (BC). BC user-modeling is a technique in which user-data, taken from observing a user’s ...