Abstract: Traditional data mining and machine learning technologies may fail when the training data and the testing data are drawn from different feature spaces and different distributions. Transfer ...

CNNs -> Convolutional Neural Networks SAR -> Synthetic Aperture Radar. This project is based on predicting the accuracy of the testing data set over the training data set using the MSTAR(Moving and ...

Objectives of AnyGraph: Structure Heterogeneity: Addressing distribution shift in graph structural information.; Feature Heterogeneity: Handling diverse feature representation spaces across graph ...

Recent advances in relation extraction with deep neural architectures have achieved excellent performance. However, current models still suffer from two main drawbacks: 1) they require enormous ...

Consider, for example, the need to expose an AI model to large amounts of data for training. When data may not yet exist or may lack comprehensiveness, synthetic data comes into the training equation.

Parallel Domain’s synthetic data platform consists of two modes: training and testing. When training, customers will describe high-level parameters — for example, highway driving with 50% rain ...