141 citations · 288 across the 11 of their papers we have counts for
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cs.LG2015★ 29 cited
Deep Learning for Multi-label Classification
Jesse Read, Fernando Perez-Cruz
In multi-label classification, the main focus has been to develop ways of learning the underlying dependencies between labels, and to take advantage of this at classification time.…
stat.ML2015★ 84 cited
Scalable Multi-Output Label Prediction: From Classifier Chains to Classifier Trellises
J. Read, L. Martino, P. Olmos +1
Multi-output inference tasks, such as multi-label classification, have become increasingly important in recent years. A popular method for multi-label classification is classifier…