A partir del momento que los diversos aspectos de la vida social (económicos, lingüísticos,
etc) se expresen como relaciones, queda abierto el camino para una antropología …

Methods and systems are provided for encoding, transmis sion and decoding of vectorized
input data, for example, Video or audio data. A convex invariance learning framework is …

We propose modeling images and related visual objects as bags of pixels or sets of vectors.
For instance, gray scale images are modeled as a collection or bag of (X, Y, I) pixel vectors …

Many functions have been recently defined to assess the similarity among networks as tools
for quantitative comparison. They stem from very different frameworks-and they are tuned for …

Despite recent progress in the analysis of neuroimaging data sets, our comprehension of the
main mechanisms and principles which govern human brain cognition and function remains …

Distributed decision making in networked systems depends critically on the timely
availability of critical fresh information. Performance of networked systems, from the …

A weighted (unweighted) graph G is called equiarboreal if the sum of weights (the number)
of spanning trees containing a given edge in G is independent of the choice of edge. In this …

In this paper, we investigate Approximate Bayes Computation as a technique for estimating
the parameters of graph generators relative to an observed graph. Specifically, we …

Through characterising a computer network as a time series of graphs, with IP addresses on
the vertices and edges weighted by the number of packets transmitted, we apply graph …

Invariance and representation learning are important precursors to modeling and
classification tools particularly for non-Euclidean spaces such as images, strings and …