This paper investigates neighborhood peer eff ects on individual welfare using a combined IV and control function approach. The empirical analysis is based on panel data for the years 2007-2010 constructed by enriching the geo-referenced version of the German Socio-Economic Panel (GSOEP) with aggregated zip code level-information. The results suggest that individual welfare use is positively co...

In this paper, we propose a new supervised Neighborhood Discriminative Manifold Projection (NDMP) method for feature extraction in video-based face recognition. The abundance of data in videos often result in highly nonlinear appearance manifolds. In order to extract good discriminative features, an optimal low-dimensional projection is learned from selected face exemplars by solving a constrai...

A Fuzzy Adaptive Neighborhood Search for Function Optimization David A. Pelta Armando Blanco Jose-L. Verdegay Depto. de Ciencias de la Computaci6n e Inteiigencia Artificial. Universidad de Granada, Granada, Spain {dpelta,armando ,verdegay}@ugr . es Neighborhood based search algorithms have been applied with success in the optimization field. In this work, a Fuzzy Adaptive Neighborhood Search al...

Predicting protein function is one of the most challenging problems of the post-genomic era. The development of experimental methods for genome scale analysis of molecular interaction networks has provided new approaches to inferring protein function. In this paper we introduce a new graph-based semi-supervised classification algorithm Sequential Linear Neighborhood Propagation (SLNP), which ad...

Two self-organizing principles for the competitive identification and segmentation of piecewise stationary time series are described. In the first, a neighborhood map of one step predictors competes for the data during training. The winner is granted the largest parameter update, while other predictors are allowed smaller updates, decreasing with distance from the winner on the neighborhood map...

Free-association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a...

A self-organizing map (SOM) algorithm can generate a topographic map from a high-dimensional stimulus space to a low-dimensional array of units. Because a topographic map preserves neighborhood relationships between the stimuli, the SOM can be applied to certain types of information processing such as data visualization. During the learning process, however, topological defects frequently emerg...