We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
While most supervised machine learning models assume that training examples are sampled at random or adversarially, this article is concerned with models of learning from a cooper...
Sandra Zilles, Steffen Lange, Robert Holte, Martin...
Unpredictability in COTS-based systems often manifests as occasional instances of uncontrollably-high response times. A particular category of COTS systems, fault-tolerant (FT) mid...
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...
The stochastic discrimination (SD) theory considers learning as building models of uniform coverage over data distributions. Despite successful trials of the derived SD method in s...