: In agglomerative hierarchical clustering, pair-group methods suffer from a problem of non-uniqueness when two or more distances between different clusters coincide during the ama...
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
Sparse representation theory has been increasingly used in the fields of signal processing and machine learning. The standard sparse models are not invariant to spatial transform...
The goal of emotion classification is to estimate an emotion label, given representative data and discriminative features. Humans are very good at deriving high-level representat...
Manual classification of free-text documents within a predefined hierarchy is highly time consuming. This is especially true for clinical guidelines, which are often indexed by mu...
Robert Moskovitch, Shiva Cohen-Kashi, Uzi Dror, If...