期刊文章：

[TPAMI 25] Shilong Bao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, and Qingming Huang. AUCPro: AUC-Oriented Provable Robustness Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 47(6): 4579-4596, Jun. 2025.  (Regular paper)

[TPAMI 24]  Peisong Wen, Qianqian Xu, Zhiyong Yang, Yuan He, and Qingming Huang. Algorithm-Dependent Generalization of AUPRC Optimization: Theory and Algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 46(7): 5062-5079, Jul. 2024. (Regular paper)

[TPAMI 23] Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao and Qingming Huang.  Optimizing Partial Area Under the Top-k Curve: Theory and Practice. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(4): 5053-5069, Apr. 2023. (Regular paper)

[TPAMI 23] Shilong Bao, Qianqian Xu, Zhiyong Yang, Xiaochun Cao and Qingming Huang. Rethinking Collaborative Metric Learning: Toward an Efficient Alternative without Negative Sampling. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(1): 1017-1035, Jan. 2023. (Regular paper)

[TPAMI 23] Qianqian Xu, Zhiyong Yang, Yunrui Zhao, Xiaochun Cao, and Qingming Huang. Rethinking Label Flipping Attack: From Sample Masking to Sample Thresholding. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(6): 7668-7685, Jun. 2023. (Regular paper)

[TPAMI 23] Zhiyong Yang, Qianqian Xu, Shilong Bao, Yuan He, Xiaochun Cao, and Qingming Huang. Optimizing Two-way Partial AUC with an End-to-end Framework. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(8): 10228-10246, Aug. 2023. (Regular paper) 

[TPAMI 22] Qianqian Xu, Zhiyong Yang, Yangbangyan Jiang, Xiaochun Cao, Yuan Yao and Qingming Huang. Not All Samples are Trustworthy: Towards Deep Robust SVP Prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 44(6): 3154-3169, Jun. 2022. (Regular paper)

[TPAMI 22] Zhiyong Yang, Qianqian Xu, Shilong Bao, Xiaochun Cao and Qingming Huang. Learning with Multiclass AUC: Theory and Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 44(11): 7747-7763, Nov. 2022. (Regular paper)

[TPAMI 21] Zhiyong Yang, Qianqian Xu, Xiaochun Cao and Qingming Huang. Task-Feature Collaborative Learning with Application to Personalized Attribute Prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 43(11): 4094-4110, Nov. 2021. (Regular paper)

[TPAMI 19] Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Qingming Huang and Yuan Yao. From Social to Individuals: A Parsimonious Path of Multi-level Models for Crowdsourced Preference Aggregation. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 41(4): 844-856, Apr. 2019. (Regular paper)

会议文章：

[ICML 25] Sicong Li, Qianqian Xu, Zhiyong Yang, Zitai Wang, Linchao Zhang, Xiaochun Cao, and Qingming Huang. Focal-SAM: Focal Sharpness-Aware Minimization for Long-Tailed Classification. International Conference on Machine Learning (ICML), 2025. 

[ICML 25] Cong Hua, Qianqian Xu, Zhiyong Yang, Zitai Wang, Shilong Bao, and Qingming Huang. OpenworldAUC: Towards Unified Evaluation and Optimization for Open-world Prompt Tuning. International Conference on Machine Learning (ICML), 2025.

[ICML 25] Feiran Li, Qianqian Xu, Shilong Bao, Zhiyong Yang, Xiaochun Cao, and Qingming Huang. One Image is Worth a Thousand Words: A Usability Preservable Text-Image Collaborative Erasing Framework for Diffusion Models. International Conference on Machine Learning (ICML), 2025. 

[ICML 24] Zhiyong Yang, Qianqian Xu, Zitai Wang, Sicong Li, Boyu Han, Shilong Bao, Xiaochun Cao, and Qingming Huang. Harnessing Hierarchical Label Distribution Variations in Test Agnostic Long-tail Recognition. International Conference on Machine Learning (ICML), 56624-56664, 2024.

[ICML 24] Feiran Li, Qianqian Xu, Shilong Bao, Zhiyong Yang, Runmin Cong, Xiaochun Cao, and Qingming Huang. Size-invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection. International Conference on Machine Learning (ICML), 28989-29021, 2024. (Spotlight)

[ICML 24] Cong Hua, Qianqian Xu, Shilong Bao, Zhiyong Yang, and Qingming Huang. ReconBoost: Boosting Can Achieve Modality Reconcilement. International Conference on Machine Learning (ICML), 19573-19597, 2024.

[NeurIPS 24] Benyuan Meng, Qianqian Xu, Zitai Wang, Xiaochun Cao, and Qingming Huang. Not All Diffusion Model Activations Have Been Evaluated as Discriminative Features. Annual Conference on Neural Information Processing Systems (NeurIPS), 55141-55177, 2024. (Spotlight)

[NeurIPS 24] Boyu Han, Qianqian Xu, Zhiyong Yang, Shilong Bao, Peisong Wen, Yangbangyan Jiang, and Qingming Huang. AUCSeg: AUC-oriented Pixel-level Long-tail Semantic Segmentation. Annual Conference on Neural Information Processing Systems (NeurIPS), 126863-126907, 2024.

[NeurIPS 24] Benyuan Meng, Qianqian Xu, Zitai Wang, Zhiyong Yang, Xiaochun Cao, and Qingming Huang. Suppress Content Shift: Better Diffusion Features via Off-the-Shelf Generation Techniques. Annual Conference on Neural Information Processing Systems (NeurIPS), 18910-18939, 2024.

[NeurIPS 23] Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, and Qingming Huang. A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning. Annual Conference on Neural Information Processing Systems (NeurIPS), 48417-48430, 2023. (Spotlight)

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