LARGE-SCALE STOCHASTIC OPTIMIZATION OF NDCG SURROGATES FOR DEEP LEARNING WITH PROVABLE CONVERGENCE

The dataset used in the paper is the MSLR-WEB30K dataset and the Yahoo! LTR dataset, which are the largest public LTR datasets from commercial search engines.

Data and Resources

Cite this as

Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Lijun Zhang, Tianbao Yang (2024). Dataset: LARGE-SCALE STOCHASTIC OPTIMIZATION OF NDCG SURROGATES FOR DEEP LEARNING WITH PROVABLE CONVERGENCE. https://doi.org/10.57702/xc61ass6

DOI retrieved: December 17, 2024

Additional Info

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Created December 17, 2024
Last update December 17, 2024
Defined In https://doi.org/10.48550/arXiv.2202.12183
Author Zi-Hao Qiu
More Authors
Quanqi Hu
Yongjian Zhong
Lijun Zhang
Tianbao Yang
Homepage https://libauc.org/