This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
A number of machine learning (ML) techniques have recently been proposed to solve color constancy problem in computer vision. Neural networks (NNs) and support vector regression (...
Graphs are widely used to model real world objects and their relationships, and large graph datasets are common in many application domains. To understand the underlying character...
Yuanyuan Tian, Richard A. Hankins, Jignesh M. Pate...
Designers of SoCs with non-digital components, such as analog or MEMS devices, can currently use high-level system design languages, such as SystemC, to model only the digital par...
Ankush Varma, Muhammad Yaqub Afridi, Akin Akturk, ...
Complex networks have been used successfully in scientific disciplines ranging from sociology to microbiology to describe systems of interacting units. Until recently, studies of...