Zi-Hao Qiu

14 papers A* 6A 1Journal 7
YearRankTypeTitle / Venue / Authors
2025 J jnl
Optimal large-scale stochastic optimization of NDCG surrogates for deep learning.
Mach. Learn.
Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Wei-Wei Tu, Lijun Zhang, Tianbao Yang
2024 A* conf
To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO.
ICML
Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang
2024 J jnl
To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO.
CoRR
Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang
2023 A* conf
Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization.
ICML
Quanqi Hu, Zi-Hao Qiu, Zhishuai Guo, Lijun Zhang, Tianbao Yang
2023 J jnl
Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization.
CoRR
Quanqi Hu, Zi-Hao Qiu, Zhishuai Guo, Lijun Zhang, Tianbao Yang
2023 A* conf
LibAUC: A Deep Learning Library for X-Risk Optimization.
KDD
Zhuoning Yuan, Dixian Zhu, Zi-Hao Qiu, Gang Li, Xuanhui Wang, Tianbao Yang
2023 J jnl
LibAUC: A Deep Learning Library for X-Risk Optimization.
CoRR
Zhuoning Yuan, Dixian Zhu, Zi-Hao Qiu, Gang Li, Xuanhui Wang, Tianbao Yang
2023 A* conf
Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization.
ICML
Zi-Hao Qiu, Quanqi Hu, Zhuoning Yuan, Denny Zhou, Lijun Zhang, Tianbao Yang
2023 J jnl
Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization.
CoRR
Zi-Hao Qiu, Quanqi Hu, Zhuoning Yuan, Denny Zhou, Lijun Zhang, Tianbao Yang
2022 A* conf
Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence.
ICML
Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Lijun Zhang, Tianbao Yang
2022 J jnl
Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence.
CoRR
Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Lijun Zhang, Tianbao Yang
2022 A* conf
Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance.
ICML
Zhuoning Yuan, Yuexin Wu, Zi-Hao Qiu, Xianzhi Du, Lijun Zhang, Denny Zhou, Tianbao Yang
2022 J jnl
Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance.
CoRR
Zhuoning Yuan, Yuexin Wu, Zi-Hao Qiu, Xianzhi Du, Lijun Zhang, Denny Zhou, Tianbao Yang
2021 A conf
Learning to Augment Imbalanced Data for Re-ranking Models.
CIKM
Zi-Hao Qiu, Ying-Chun Jian, Qing-Guo Chen, Lijun Zhang