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Azad Naik
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2010 – 2019
- 2019
- [j3]Azad Naik, Huzefa Rangwala:
Improving large-scale hierarchical classification by rewiring: a data-driven filter based approach. J. Intell. Inf. Syst. 52(1): 141-164 (2019) - 2018
- [b2]Azad Naik:
Hierarchical Classification with Rare Categories and Inconsistencies. George Mason University, Fairfax, VA, USA, 2018 - [b1]Azad Naik, Huzefa Rangwala:
Large Scale Hierarchical Classification: State of the Art. Springer Briefs in Computer Science, Springer 2018, ISBN 978-3-030-01619-7, pp. 1-93 - 2017
- [j2]Azad Naik, Huzefa Rangwala:
HierFlat: flattened hierarchies for improving top-down hierarchical classification. Int. J. Data Sci. Anal. 4(3): 191-208 (2017) - [c5]Azad Naik, Huzefa Rangwala:
Integrated Framework for Improving Large-Scale Hierarchical Classification. ICMLA 2017: 281-288 - [i4]Azad Naik, Huzefa Rangwala:
Inconsistent Node Flattening for Improving Top-down Hierarchical Classification. CoRR abs/1706.01214 (2017) - [i3]Azad Naik, Huzefa Rangwala:
Embedding Feature Selection for Large-scale Hierarchical Classification. CoRR abs/1706.01581 (2017) - [i2]Azad Naik, Anveshi Charuvaka, Huzefa Rangwala:
Classifying Documents within Multiple Hierarchical Datasets using Multi-Task Learning. CoRR abs/1706.01583 (2017) - 2016
- [j1]Azad Naik, Huzefa Rangwala:
Large-scale hierarchical classification with rare categories and inconsistencies. AI Matters 2(3): 27-29 (2016) - [c4]Azad Naik, Huzefa Rangwala:
Embedding feature selection for large-scale hierarchical classification. IEEE BigData 2016: 1212-1221 - [c3]Azad Naik, Huzefa Rangwala:
Inconsistent Node Flattening for Improving Top-Down Hierarchical Classification. DSAA 2016: 379-388 - [i1]Azad Naik, Huzefa Rangwala:
Filter based Taxonomy Modification for Improving Hierarchical Classification. CoRR abs/1603.00772 (2016) - 2015
- [c2]Azad Naik, Huzefa Rangwala:
A ranking-based approach for hierarchical classification. DSAA 2015: 1-10 - 2013
- [c1]Azad Naik, Anveshi Charuvaka, Huzefa Rangwala:
Classifying Documents within Multiple Hierarchical Datasets Using Multi-task Learning. ICTAI 2013: 390-397
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