Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
A common problem in the operation of mission critical control systems is that of determining the future value of a physical quantity based upon past measurements of it or of relat...
This paper presents a new approach to understand the event stream model. Additionally a new approximation algorithm for the feasibility test of the sporadic and the generalized mu...
— With the continuing downscaling of microelectronic technology, chip reliability becomes a great threat to the design of future complex microelectronic systems. Hence increasing...
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...