68 citations · 131 across the 3 of their papers we have counts for
3 papers
DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents
Kunal Dahiya, Deepak Saini, Anshul Mittal +6
Scalability and accuracy are well recognized challenges in deep extreme multi-label learning where the objective is to train architectures for automatically annotating a data point…
DECAF: Deep Extreme Classification with Label Features
Anshul Mittal, Kunal Dahiya, Sheshansh Agrawal +4
Extreme multi-label classification (XML) involves tagging a data point with its most relevant subset of labels from an extremely large label set, with several applications such as…
ECLARE: Extreme Classification with Label Graph Correlations
Anshul Mittal, Noveen Sachdeva, Sheshansh Agrawal +3
Deep extreme classification (XC) seeks to train deep architectures that can tag a data point with its most relevant subset of labels from an extremely large label set. The core uti…