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Sujay Khandagale
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2020 – today
- 2023
- [c8]Duncan C. McElfresh, Sujay Khandagale, Jonathan Valverde, Vishak Prasad C., Ganesh Ramakrishnan, Micah Goldblum, Colin White:
When Do Neural Nets Outperform Boosted Trees on Tabular Data? NeurIPS 2023 - [i4]Duncan C. McElfresh, Sujay Khandagale, Jonathan Valverde, Vishak Prasad C., Ganesh Ramakrishnan, Micah Goldblum, Colin White:
When Do Neural Nets Outperform Boosted Trees on Tabular Data? CoRR abs/2305.02997 (2023) - 2022
- [c7]Sujay Khandagale, Yoann Léveillé, Samuel Miller, Derek Pham, Ramy Eskander, Cass Lowry, Richard Compton, Judith Klavans, Maria Polinsky, Smaranda Muresan:
Towards Unsupervised Morphological Analysis of Polysynthetic Languages. AACL/IJCNLP (2) 2022: 334-340 - [c6]Ramy Eskander, Cass Lowry, Sujay Khandagale, Judith Klavans, Maria Polinsky, Smaranda Muresan:
Unsupervised Stem-based Cross-lingual Part-of-Speech Tagging for Morphologically Rich Low-Resource Languages. NAACL-HLT 2022: 4061-4072 - [c5]Duncan C. McElfresh, Sujay Khandagale, Jonathan Valverde, John Dickerson, Colin White:
On the Generalizability and Predictability of Recommender Systems. NeurIPS 2022 - [i3]Duncan C. McElfresh, Sujay Khandagale, Jonathan Valverde, John P. Dickerson, Colin White:
On the Generalizability and Predictability of Recommender Systems. CoRR abs/2206.11886 (2022) - 2021
- [c4]Ramy Eskander, Cass Lowry, Sujay Khandagale, Francesca Callejas, Judith Klavans, Maria Polinsky, Smaranda Muresan:
Minimally-Supervised Morphological Segmentation using Adaptor Grammars with Linguistic Priors. ACL/IJCNLP (Findings) 2021: 3969-3974 - [c3]Yang Liu, Sujay Khandagale, Colin White, Willie Neiswanger:
Synthetic Benchmarks for Scientific Research in Explainable Machine Learning. NeurIPS Datasets and Benchmarks 2021 - [i2]Yang Liu, Sujay Khandagale, Colin White, Willie Neiswanger:
Synthetic Benchmarks for Scientific Research in Explainable Machine Learning. CoRR abs/2106.12543 (2021) - 2020
- [j1]Sujay Khandagale, Han Xiao, Rohit Babbar
:
Bonsai: diverse and shallow trees for extreme multi-label classification. Mach. Learn. 109(11): 2099-2119 (2020) - [c2]Mohammadreza Qaraei, Sujay Khandagale, Rohit Babbar:
Why state-of-the-art deep learning barely works as good as a linear classifier in extreme multi-label text classification. ESANN 2020: 223-228
2010 – 2019
- 2019
- [c1]Sujay Khandagale, Rohit Babbar:
A Simple and Effective Scheme for Data Pre-processing in Extreme Classification. ESANN 2019 - [i1]Sujay Khandagale
Bonsai - Diverse and Shallow Trees for Extreme Multi-label Classification. CoRR abs/1904.08249 (2019)
Coauthor Index
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