We study the common problem of approximating a target matrix with a matrix of lower rank. We provide a simple and efficient (EM) algorithm for solving weighted low-rank approximat...
We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other u...
We propose a deterministic method to evaluate the integral of a positive function based on soft-binning functions that smoothly cut the integral into smaller integrals that are ea...
—We propose a Smart Trend-Traversal (STT) protocol for RFID tag arbitration, which effectively reduces the collision overhead occurred in the arbitration process. STT, a Query Tr...
The paper presents a novel Motor Map neural network for re-indexing color mapped images. The overall learning process is able to smooth the local spatial redundancy of the indexes ...
Sebastiano Battiato, Francesco Rundo, Filippo Stan...