482 citations · 727 across the 36 of their papers we have counts for
4 papers · 1 filter
Adopting Robustness and Optimality in Fitting and Learning
Zhiguang Wang, Tim Oates, James Lo
We generalized a modified exponentialized estimator by pushing the robust-optimal (RO) index to for achieving robustness to outliers by optimizing a quasi-Minimin fun…
Spatially Encoding Temporal Correlations to Classify Temporal Data Using Convolutional Neural Networks
Zhiguang Wang, Tim Oates
We propose an off-line approach to explicitly encode temporal patterns spatially as different types of images, namely, Gramian Angular Fields and Markov Transition Fields. This ena…
Adaptive Normalized Risk-Averting Training For Deep Neural Networks
Zhiguang Wang, Tim Oates, James Lo
This paper proposes a set of new error criteria and learning approaches, Adaptive Normalized Risk-Averting Training (ANRAT), to attack the non-convex optimization problem in traini…
Imaging Time-Series to Improve Classification and Imputation
Zhiguang Wang, Tim Oates
Inspired by recent successes of deep learning in computer vision, we propose a novel framework for encoding time series as different types of images, namely, Gramian Angular Summat…