New fashion product sales forecasting is a challenging problem that involves many business
dynamics and cannot be solved by classical forecasting approaches. In this paper, we …

Biclustering represents an intrinsically complex problem, where the aim is to perform a
simultaneous row- and column-clustering of a given data matrix. Some recent approaches model …

We present Visuelle 2.0, the first dataset useful for facing diverse prediction problems that a
fast-fashion company has to manage routinely. Furthermore, we demonstrate how the use of …

In many scientific areas, it is crucial to group (cluster) a set of objects, based on a set of observed
features. Such operation is widely known as Clustering and it has been exploited in the …

Several problem in Artificial Intelligence and Pattern Recognition are computationally
intractable due to their inherent complexity and the exponential size of the solution space. One …

Multiple Structure Recovery (MSR) represents an important and challenging problem in the
field of Computer Vision and Pattern Recognition. Recent approaches to MSR advocate the …

We propose an automatic system aimed at discovering relevant activities for aquatic drones
employed in water monitoring applications. The methodology exploits unsupervised time …

Biclustering is an intrinsically challenging and highly complex problem, particularly studied
in the biology field, where the goal is to simultaneously cluster genes and samples of an …

Biclustering refers to the problem of simultaneously clustering the rows and columns of a
given data matrix, with the goal of obtaining submatrices where the selected rows present a …

Biclustering can be defined as the simultaneous clustering of rows and columns in a data
matrix and it has been recently applied to many scientific scenarios such as bioinformatics, text …