Despite considerable effort, the state-space explosion problem remains an issue in the analysis of Markov models. Given structure, symbolic representations can result in very comp...
Marta Z. Kwiatkowska, Rashid Mehmood, Gethin Norma...
Kernel principal component analysis (KPCA) extracts features of samples with an efficiency in inverse proportion to the size of the training sample set. In this paper, we develop...
Yong Xu, David Zhang, Fengxi Song, Jing-Yu Yang, Z...
A large number of problems that occur in knowledge-representation, learning, VLSI-design, and other areas of artificial intelligence, are essentially satisfiability problems. The ...
Additive clustering was originally developed within cognitive psychology to enable the development of featural models of human mental representation. The representational flexibili...
We present a readily applicable way to go beyond the accuracy limits of current optical flow estimators. Modern optical flow algorithms employ the coarse to fine approach. We s...