A general-purpose object indexingtechnique is described that combines the virtues of principal component analysis with the favorable matching properties of high-dimensional spaces...
An important task in data analysis is the discovery of causal relationships between observed variables. For continuous-valued data, linear acyclic causal models are commonly used ...
— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
—We apply large deviations theory to study asymptotic performance of running consensus distributed detection in sensor networks. Running consensus is a stochastic approximation t...
Error estimation must be used to find the accuracy of a designed classifier, an issue that is critical in biomarker discovery for disease diagnosis and prognosis in genomics and p...
Amin Zollanvari, Ulisses Braga-Neto, Edward R. Dou...