activity
20192025
most citedBonsai -- Diverse and Shallow Trees for Extreme Multi-label Classification

114 citations · 207 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR2025★ 1 cited

InteractRank: Personalized Web-Scale Search Pre-Ranking with Cross Interaction Features

Sujay Khandagale, Bhawna Juneja, Prabhat Agarwal +3

Modern search systems use a multi-stage architecture to deliver personalized results efficiently. Key stages include retrieval, pre-ranking, full ranking, and blending, which refin…

cs.LG2023★ 71 cited

When Do Neural Nets Outperform Boosted Trees on Tabular Data?

Duncan McElfresh, Sujay Khandagale, Jonathan Valverde +6

Tabular data is one of the most commonly used types of data in machine learning. Despite recent advances in neural nets (NNs) for tabular data, there is still an active discussion…

cs.IR2022★ 4 cited

On the Generalizability and Predictability of Recommender Systems

Duncan McElfresh, Sujay Khandagale, Jonathan Valverde +2

While other areas of machine learning have seen more and more automation, designing a high-performing recommender system still requires a high level of human effort. Furthermore, r…

cs.LG2021★ 17 cited

Synthetic Benchmarks for Scientific Research in Explainable Machine Learning

Yang Liu, Sujay Khandagale, Colin White +1

As machine learning models grow more complex and their applications become more high-stakes, tools for explaining model predictions have become increasingly important. This has spu…

cs.LG2019★ 114 cited

Bonsai -- Diverse and Shallow Trees for Extreme Multi-label Classification

Sujay Khandagale, Han Xiao, Rohit Babbar

Extreme multi-label classification (XMC) refers to supervised multi-label learning involving hundreds of thousand or even millions of labels. In this paper, we develop a suite of a…