Abstract. We develop a probabilistic interpretation of non-linear component extraction in neural networks that activate their hidden units according to a softmaxlike mechanism. On ...
We study a generative model in which hidden causes combine competitively to produce observations. Multiple active causes combine to determine the value of an observed variable thr...
Abstract. Nonlinear component analysis is a popular nonlinear feature extraction method. It generally uses eigen-decomposition technique to extract the principal components. But th...
We present a hybrid and parallel system based on artificial neural networks for a face invariant classifier and general pattern recognition problems. A set of face features is ext...
Peter V. Bazanov, Tae-Kyun Kim, Seok-Cheol Kee, Sa...
—We study scalable routing for a sensor network deployed in complicated 3D settings such as underground tunnels in gas system or water system. The nodes are in general 3D space b...
Xiaokang Yu, Xiaotian Yin, Wei Han, Jie Gao, Xianf...