Assembly output codes for learning neural networks

• Published in: 2016 9th International Symposium on Turbo Codes and Iterative Information Processing (ISTC) pp. 285 - 289
• Main Authors: Tigreat, Philippe, Lassance, Carlos Rosar Kos, Xiaoran Jiang, Gripon, Vincent, Berrou, Claude
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.09.2016
• Subjects: Assembly coding; Classification; Clustered Clique Networks; Coding theory; Deep Learning; ECOC

Neural network-based classifiers usually encode the class labels of input data via a completely disjoint code, i.e. a binary vector with only one bit associated with each category. We use coding theory to propose assembly codes where each element is associated with several classes, making for better...