Despite great efforts on the design of ultra-reliable components, the increase of system size and complexity has outpaced the improvement of component reliability. As a result, fa...
Jiexing Gu, Ziming Zheng, Zhiling Lan, John White,...
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
Predictive toxicology is the task of building models capable of determining, with a certain degree of accuracy, the toxicity of chemical compounds. Machine Learning (ML) in general...
Schema learning is a way to discover probabilistic, constructivist, predictive action models (schemas) from experience. It includes methods for finding and using hidden state to m...
Time varying environments or model selection problems lead to crucial dilemmas in identification and control science. In this paper, we propose a modular prediction scheme consisti...