D imensionality reduction is one of the basic operations in the toolbox of data analysts and designers of ma chine learning and pattern recognition systems. Given a large set of measured variables but few observations, an obvious idea is to reduce the degrees of freedom in the measurements by representing them with a smaller set of more “condensed” variables. Another reason for reducing the dim...

Dimensionality reduction is one of the basic operations in the toolbox of data-analysts and designers of machine learning and pattern recognition systems. Given a large set of measured variables but few observations, an obvious idea is to reduce the degrees of freedom in the measurements by representing them with a smaller set of more “condensed” variables. Another reason for reducing the dimen...

We studied mechanisms underlying the crowding effect in indirect form vision by measuring recognition contrast sensitivity of a character with flankers to the left and right. Attentional and featural contributions to the effect can be separated by a new paradigm that distinguishes pattern location errors from pattern recognition errors and further by manipulating the focusing of spatial attenti...

Multi-Layer Perceptrons (MLPs) have proven to be an e ective way to solve classi cation tasks. A major concern in their use is the di culty to de ne the proper network for a speci c application, due to the sensitivity to the initial conditions and to over tting and under tting problems which limit their generalization capability. Moreover, time and hardware constraints may seriously reduce the ...

One of the fundamental rights of patients is to have their privacy protected by health care organizations, so that information that can be used to identify a particular individual is not used to reveal sensitive patient data such as diagnoses, reasons for ordering tests, test results, etc. A common practice is to remove sensitive data from databases that are disseminated to the public, but this...

In this paper, characterizations of the degree to which a mapping $mathcal{T} : L^{X}longrightarrow M$ is an $(L, M)$-fuzzy topology are studied in detail.What is more, the degree to which an $L$-subset is an $L$-open set with respect to $mathcal{T}$ is introduced.Based on that, the degrees to which a mapping $f: Xlongrightarrow Y$ is continuous,open, closed or a quotient mapping with respect t...