A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...
Pablo Sprechmann, Ignacio Ramirez, Guillermo Sapir...
Abstract. This paper presents a novel approach for object segmentation in medical images that respects the topological relationships of multiple structures as given by a template. ...
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Nowadays, graph-based knowledge discovery algorithms do not consider numeric attributes (they are discarded in the preprocessing step, or they are treated as alphanumeric values w...
Oscar E. Romero, Jesus A. Gonzalez, Lawrence B. Ho...
Most question-answering systems contain a classifier module which determines a question category, based on which each question is assigned an answer type. However, setting up synt...
Danica Damljanovic, Milan Agatonovic, Hamish Cunni...