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Bhawna Paliwal

2 accepted papers

2024

Enhancing Tail Performance in Extreme Classifiers by Label Variance Reduction

ICLR 2024poster

Extreme Classification (XC) architectures, which utilize a massive One-vs-All (OvA) classifier layer at the output, have demonstrated remarkable performance on problems with large label sets. Nonetheless, these architectures falter on tail labels with few representative samples. This phenomenon has…

Cited by 7SourcePDFScholar
2024

OAK: Enriching Document Representations using Auxiliary Knowledge for Extreme Classification

ICML 2024poster

The objective in eXtreme Classification (XC) is to find relevant labels for a document from an exceptionally large label space. Most XC application scenarios have rich auxiliary data associated with the input documents, e.g., frequently clicked webpages for search queries in sponsored search. Unfort…

Cited by 2SourcePDFScholar