Quanqi Hu

According to our database, Quanqi Hu authored at least 8 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Optimal large-scale stochastic optimization of NDCG surrogates for deep learning.

Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Wei-Wei Tu, Lijun Zhang, Tianbao Yang

Mach. Learn., January, 2025

2024

Provable Optimization for Adversarial Fair Self-supervised Contrastive Learning.

Qi Qi, Quanqi Hu, Qihang Lin, Tianbao Yang

CoRR, 2024

Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions.

Quanqi Hu, Qi Qi, Zhaosong Lu, Tianbao Yang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization.

Quanqi Hu, Dixian Zhu, Tianbao Yang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization.

Zi-Hao Qiu, Quanqi Hu, Zhuoning Yuan, Denny Zhou, Lijun Zhang, Tianbao Yang

Proceedings of the International Conference on Machine Learning, 2023

Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization.

Quanqi Hu, Zi-Hao Qiu, Zhishuai Guo, Lijun Zhang, Tianbao Yang

Proceedings of the International Conference on Machine Learning, 2023

2022

Multi-block Min-max Bilevel Optimization with Applications in Multi-task Deep AUC Maximization.

Quanqi Hu, Yongjian Zhong, Tianbao Yang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence.

Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Lijun Zhang, Tianbao Yang

Proceedings of the International Conference on Machine Learning, 2022