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2020 – today
- 2024
[c7]Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang:
To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO. ICML 2024- [i6]Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang:
To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO. CoRR abs/2404.04575 (2024) - 2023
- [c6]Quanqi Hu, Zi-Hao Qiu, Zhishuai Guo, Lijun Zhang, Tianbao Yang:
Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization. ICML 2023: 13550-13583 - [c5]Zi-Hao Qiu, Quanqi Hu, Zhuoning Yuan, Denny Zhou, Lijun Zhang, Tianbao Yang:
Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization. ICML 2023: 28389-28421 - [c4]Zhuoning Yuan
, Dixian Zhu, Zi-Hao Qiu, Gang Li, Xuanhui Wang, Tianbao Yang:
LibAUC: A Deep Learning Library for X-Risk Optimization. KDD 2023: 5487-5499 - [i5]Zi-Hao Qiu, Quanqi Hu, Zhuoning Yuan, Denny Zhou, Lijun Zhang, Tianbao Yang:
Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization. CoRR abs/2305.11965 (2023) - [i4]Quanqi Hu, Zi-Hao Qiu, Zhishuai Guo, Lijun Zhang, Tianbao Yang:
Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization. CoRR abs/2305.18730 (2023) - [i3]Zhuoning Yuan, Dixian Zhu, Zi-Hao Qiu, Gang Li, Xuanhui Wang, Tianbao Yang:
LibAUC: A Deep Learning Library for X-Risk Optimization. CoRR abs/2306.03065 (2023) - 2022
- [c3]Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Lijun Zhang, Tianbao Yang:
Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence. ICML 2022: 18122-18152 - [c2]Zhuoning Yuan, Yuexin Wu, Zi-Hao Qiu, Xianzhi Du, Lijun Zhang, Denny Zhou, Tianbao Yang:
Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance. ICML 2022: 25760-25782 - [i2]Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Lijun Zhang, Tianbao Yang:
Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence. CoRR abs/2202.12183 (2022) - [i1]Zhuoning Yuan, Yuexin Wu, Zi-Hao Qiu, Xianzhi Du, Lijun Zhang, Denny Zhou, Tianbao Yang:
Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance. CoRR abs/2202.12387 (2022) - 2021
- [c1]Zi-Hao Qiu, Ying-Chun Jian, Qing-Guo Chen, Lijun Zhang:
Learning to Augment Imbalanced Data for Re-ranking Models. CIKM 2021: 1478-1487
Coauthor Index
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