stock selection method in stock exchange is an important issue for investors in such markets. investors will gain benefits more than market average provided that they make logical decisions while selecting stocks. the issue of stock selection in markets like tehran stock exchange (that are not so efficient) is requires more attention of the investors as there is not a suitable equilibrium betwe...

We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while off-diagonal blocks are approximated. Partitioning input data points, we present a two-layer hierarchical model for GP regression, where prototypes of clusters in the upper layer are involved for coarse modeling by a GP...

between of effective factors in agricultural crops production, climatic conditions is an important task from the view of environmental variables. on the other hand the basic in agricultural development is having detailed knowledge of the environmental characteristics in any place and applying specific management. saffron as the world's most valuable agricultural and medicinal product is among t...

objectives: to locate the road emergency stations in fars province based on using spatial multi-criteria decision making (delphi method).    methods: in this study, the criteria affecting the location of road emergency stations have been identified through delphi method and their importance was determined using analytical hierarchical process (ahp). with regard to the importance of the criteria...

The Hierarchical Dirichlet process is a discrete random measure serving as an important prior in Bayesian non-parametrics. It motivated with the study of groups clustered data. Each group modelled through level two and all share same base distribution which itself drawn from one process. has concentration parameters at each level. main results paper are law large numbers deviations for hierarch...

The Hierarchical Dirichlet Process (HDP) is a Bayesian nonparametric prior for grouped data, such as collections of documents, where each group is a mixture of a set of shared mixture densities, or topics, where the number of topics is not fixed, but grows with data size. The Nested Dirichlet Process (NDP) builds on the HDP to cluster the documents, but allowing them to choose only from a set o...

q-mode hierarchical cluster (hca) and principal component analysis (pca) were simultaneously applied to groundwater hydrochemical data from the three times in 2004: june, september, and december, along the ain azel aquifer, algeria, to extract principal factors corresponding to the different sources of variation in the hydrochemistry, with the objective of defining the main controls on the h...