We propose a new theoretical framework for generalizing the traditional notion of covariance. First, we discuss the role of pairwise cross-cumulants by introducing a cluster expan...
In this paper, we propose a new data reduction algorithm that iteratively selects some samples and ignores others that can be absorbed, or represented, by those selected. This alg...
A novel and general criterion for image similarity validation is introduced using the so-called a contrario decision framework. It is mathematically proved that it is possible to c...
Many real-world problems are characterized by complex relational structure, which can be succinctly represented in firstorder logic. However, many relational inference algorithms ...
Neural decoding is an important task for understanding how the biological nervous system performs computation and communication. This paper introduces a novel continuous neural de...