Quanqi Hu

20 papers A* 6Journal 13Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Single-loop Algorithms for Stochastic Non-Convex Optimization with Weakly-Convex Constraints.
Trans. Mach. Learn. Res.
Ming Yang, Gang Li, Quanqi Hu, Qihang Lin, Tianbao Yang
2025 J jnl
Learning to Rank with Top-
CoRR
Boyang Zhang, Quanqi Hu, Mingxuan Sun, Qihang Lin, Tianbao Yang
2025 J jnl
Learning to Rank with Top-$K$ Fairness.
Trans. Mach. Learn. Res.
Boyang Zhang, Quanqi Hu, Mingxuan Sun, Qihang Lin, Tianbao Yang
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
2025 J jnl
Single-loop Algorithms for Stochastic Non-convex Optimization with Weakly-Convex Constraints.
CoRR
Ming Yang, Gang Li, Quanqi Hu, Qihang Lin, Tianbao Yang
2025 J jnl
Stochastic Momentum Methods for Non-smooth Non-Convex Finite-Sum Coupled Compositional Optimization.
CoRR
Xingyu Chen, Bokun Wang, Min Yang, Quanqi Hu, Qihang Lin, Tianbao Yang
2024 — conf
Enhancing 3D Cardiac CT Segmentation with Latent Diffusion Model and Self-Supervised Learning.
ML4H@NeurIPS
Quanqi Hu, Ashok Vardhan Addala, Masaki Ikuta, Ravi Soni, Gopal Avinash
2024 J jnl
Provable Optimization for Adversarial Fair Self-supervised Contrastive Learning.
CoRR
Qi Qi, Quanqi Hu, Qihang Lin, Tianbao Yang
2024 A* conf
Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions.
NeurIPS
Quanqi Hu, Qi Qi, Zhaosong Lu, Tianbao Yang
2024 J jnl
Single-loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions.
CoRR
Quanqi Hu, Qi Qi, Zhaosong Lu, 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
Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization.
NeurIPS
Quanqi Hu, Dixian Zhu, Tianbao Yang
2023 J jnl
Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization.
CoRR
Quanqi Hu, Dixian Zhu, 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
Multi-block Min-max Bilevel Optimization with Applications in Multi-task Deep AUC Maximization.
NeurIPS
Quanqi Hu, Yongjian Zhong, Tianbao Yang
2022 J jnl
Multi-block Min-max Bilevel Optimization with Applications in Multi-task Deep AUC Maximization.
CoRR
Quanqi Hu, Yongjian Zhong, Tianbao Yang