Cibin George

Learn More
The underlying assumption in traditional machine learning algorithms is that instances are Independent and Identically Distributed (IID). These critical independence assumptions made in traditional machine learning algorithms prevent them from going beyond instance boundaries to exploit latent relations between features. In this paper, we develop a general(More)
  • 1