4 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2017
Classifying Documents within Multiple Hierarchical Datasets using Multi-Task Learning
Azad Naik, Anveshi Charuvaka, Huzefa Rangwala
Multi-task learning (MTL) is a supervised learning paradigm in which the prediction models for several related tasks are learned jointly to achieve better generalization performanc…
cs.LG2017
Inconsistent Node Flattening for Improving Top-down Hierarchical Classification
Azad Naik, Huzefa Rangwala
Large-scale classification of data where classes are structurally organized in a hierarchy is an important area of research. Top-down approaches that exploit the hierarchy during t…
cs.AI2016★ 4 cited
Filter based Taxonomy Modification for Improving Hierarchical Classification
Azad Naik, Huzefa Rangwala
Hierarchical Classification (HC) is a supervised learning problem where unlabeled instances are classified into a taxonomy of classes. Several methods that utilize the hierarchical…