This paper investigates how the Univariate Marginal Distribution Algorithm (UMDA) behaves in non-stationary environments when engaging in sampling and selection strategies designe...
for ideas, and then abstract away from these ideas to produce algorithmic processes that can create problem solutions in a bottom-up manner. We have previously described a top-dow...
Although memory-based classifiers offer robust classification performance, their widespread usage on embedded devices is hindered due to the device's limited memory resources...
In the Sesame framework, we develop a modeling and simulation environment for the efficient design space exploration of heterogeneous embedded systems. Since Sesame recognizes se...
Background: Prediction of disulfide bridges from protein sequences is useful for characterizing structural and functional properties of proteins. Several methods based on differen...
Marc Vincent, Andrea Passerini, Matthieu Labb&eacu...