Huang, Sheng-Jun

54 publications

IJCAI 2025 DM-POSA: Enhancing Open-World Test-Time Adaptation with Dual-Mode Matching and Prompt-Based Open Set Adaptation Shiji Zhao, Shao-Yuan Li, Chuanxing Geng, Sheng-Jun Huang, Songcan Chen

ICML 2025 Efficient Heterogeneity-Aware Federated Active Data Selection Ying-Peng Tang, Chao Ren, Xiaoli Tang, Sheng-Jun Huang, Lizhen Cui, Han Yu

IJCAI 2025 FedDLAD: A Federated Learning Dual-Layer Anomaly Detection Framework for Enhancing Resilience Against Backdoor Attacks Binbin Ding, Penghui Yang, Sheng-Jun Huang

AAAI 2025 Improving Generalization of Deep Neural Networks by Optimum Shifting Yuyan Zhou, Ye Li, Lei Feng, Sheng-Jun Huang

IJCAI 2025 Inconsistency-Based Federated Active Learning Chen-Chen Zong, Tong Jin, Sheng-Jun Huang

TMLR 2025 Interactive Large Language Models for Reliable Answering Under Incomplete Context Jing-Cheng Pang, Heng-Bo Fan, Pengyuan Wang, Jia-Hao Xiao, Nan Tang, Si-Hang Yang, Chengxing Jia, Ming-Kun Xie, Xiang Chen, Sheng-Jun Huang, Yang Yu

ICML 2025 Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang, Sheng-Jun Huang

AAAI 2025 MLC-NC: Long-Tailed Multi-Label Image Classification Through the Lens of Neural Collapse Zijian Tao, Shao-Yuan Li, Wenhai Wan, Jinpeng Zheng, Jia-Yao Chen, Yuchen Li, Sheng-Jun Huang, Songcan Chen

NeurIPS 2025 Representation-Level Counterfactual Calibration for Debiased Zero-Shot Recognition Pei Peng, Ming-Kun Xie, Hang Hao, Tong Jin, Sheng-Jun Huang

CVPR 2025 Rethinking Epistemic and Aleatoric Uncertainty for Active Open-Set Annotation: An Energy-Based Approach Chen-Chen Zong, Sheng-Jun Huang

AAAI 2025 StructSR: Refuse Spurious Details in Real-World Image Super-Resolution Yachao Li, Dong Liang, Tianyu Ding, Sheng-Jun Huang

ECCV 2024 Bidirectional Uncertainty-Based Active Learning for Open-Set Annotation Chen-Chen Zong, Ye-Wen Wang, Kun-Peng Ning, Hai-Bo Ye, Sheng-Jun Huang

IJCAI 2024 Causality-Enhanced Discreted Physics-Informed Neural Networks for Predicting Evolutionary Equations Ye Li, Siqi Chen, Bin Shan, Sheng-Jun Huang

ICML 2024 Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training Ming-Kun Xie, Jia-Hao Xiao, Pei Peng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang

AAAI 2024 Dirichlet-Based Prediction Calibration for Learning with Noisy Labels Chen-Chen Zong, Ye-Wen Wang, Ming-Kun Xie, Sheng-Jun Huang

ECCV 2024 Dual-Decoupling Learning and Metric-Adaptive Thresholding for Semi-Supervised Multi-Label Learning Jia-Hao Xiao, Ming-Kun Xie, Heng-Bo Fan, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang

IJCAI 2024 NanoAdapt: Mitigating Negative Transfer in Test Time Adaptation with Extremely Small Batch Sizes Shiji Zhao, Shao-Yuan Li, Sheng-Jun Huang

ICLR 2024 One-Shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models Sheng-Jun Huang, Yi Li, Yiming Sun, Ying-Peng Tang

NeurIPS 2024 Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang, Sheng-Jun Huang

AAAI 2024 Unlocking the Power of Open Set: A New Perspective for Open-Set Noisy Label Learning Wenhai Wan, Xinrui Wang, Ming-Kun Xie, Shao-Yuan Li, Sheng-Jun Huang, Songcan Chen

IJCAI 2023 ALL-E: Aesthetics-Guided Low-Light Image Enhancement Ling Li, Dong Liang, Yuanhang Gao, Sheng-Jun Huang, Songcan Chen

NeurIPS 2023 Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning Ming-Kun Xie, Jiahao Xiao, Hao-Zhe Liu, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang

ICLRW 2023 Co-Imitation Learning Without Expert Demonstration Kun-Peng Ning, Hu Xu, Kun Zhu, Sheng-Jun Huang

AAAI 2023 Implicit Stochastic Gradient Descent for Training Physics-Informed Neural Networks Ye Li, Songcan Chen, Sheng-Jun Huang

ICCV 2023 Improving Lens Flare Removal with General-Purpose Pipeline and Multiple Light Sources Recovery Yuyan Zhou, Dong Liang, Songcan Chen, Sheng-Jun Huang, Shuo Yang, Chongyi Li

MLJ 2023 Learning from Crowds with Sparse and Imbalanced Annotations Ye Shi, Shao-Yuan Li, Sheng-Jun Huang

ICCV 2023 Multi-Label Knowledge Distillation Penghui Yang, Ming-Kun Xie, Chen-Chen Zong, Lei Feng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang

NeurIPS 2022 Active Learning for Multiple Target Models Ying-Peng Tang, Sheng-Jun Huang

CVPR 2022 Active Learning for Open-Set Annotation Kun-Peng Ning, Xun Zhao, Yu Li, Sheng-Jun Huang

NeurIPS 2022 Can Adversarial Training Be Manipulated by Non-Robust Features? Lue Tao, Lei Feng, Hongxin Wei, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen

MLJ 2022 Improving Deep Label Noise Learning with Dual Active Label Correction Shaoyuan Li, Ye Shi, Sheng-Jun Huang, Songcan Chen

NeurIPS 2022 Label-Aware Global Consistency for Multi-Label Learning with Single Positive Labels Ming-Kun Xie, Jiahao Xiao, Sheng-Jun Huang

IJCAI 2021 Asynchronous Active Learning with Distributed Label Querying Sheng-Jun Huang, Chen-Chen Zong, Kun-Peng Ning, Haibo Ye

NeurIPS 2021 Better Safe than Sorry: Preventing Delusive Adversaries with Adversarial Training Lue Tao, Lei Feng, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen

IJCAI 2021 Dual Active Learning for Both Model and Data Selection Ying-Peng Tang, Sheng-Jun Huang

AAAI 2021 Improving Model Robustness by Adaptively Correcting Perturbation Levels with Active Queries Kun-Peng Ning, Lue Tao, Songcan Chen, Sheng-Jun Huang

NeurIPS 2021 Multi-Label Learning with Pairwise Relevance Ordering Ming-Kun Xie, Sheng-Jun Huang

AAAI 2020 Active Learning with Query Generation for Cost-Effective Text Classification Yifan Yan, Sheng-Jun Huang, Shaoyi Chen, Meng Liao, Jin Xu

ICML 2020 Cost-Effectively Identifying Causal Effects When Only Response Variable Is Observable Tian-Zuo Wang, Xi-Zhu Wu, Sheng-Jun Huang, Zhi-Hua Zhou

AAAI 2020 Partial Multi-Label Learning with Noisy Label Identification Ming-Kun Xie, Sheng-Jun Huang

AAAI 2020 Uncertainty Aware Graph Gaussian Process for Semi-Supervised Learning Zhao-Yang Liu, Shaoyuan Li, Songcan Chen, Yao Hu, Sheng-Jun Huang

AAAI 2019 Active Sampling for Open-Set Classification Without Initial Annotation Zhao-Yang Liu, Sheng-Jun Huang

IJCAI 2019 Multi-View Active Learning for Video Recommendation Jia-Jia Cai, Jun Tang, Qing-Guo Chen, Yao Hu, Xiaobo Wang, Sheng-Jun Huang

AAAI 2019 Self-Paced Active Learning: Query the Right Thing at the Right Time Ying-Peng Tang, Sheng-Jun Huang

IJCAI 2018 Cost-Effective Active Learning for Hierarchical Multi-Label Classification Yifan Yan, Sheng-Jun Huang

AAAI 2018 Dual Set Multi-Label Learning Chong Liu, Peng Zhao, Sheng-Jun Huang, Yuan Jiang, Zhi-Hua Zhou

AAAI 2018 Partial Multi-Label Learning Ming-Kun Xie, Sheng-Jun Huang

IJCAI 2017 Cost-Effective Active Learning from Diverse Labelers Sheng-Jun Huang, Jia-Lve Chen, Xin Mu, Zhi-Hua Zhou

IJCAI 2017 Multi-Instance Multi-Label Active Learning Sheng-Jun Huang, Nengneng Gao, Songcan Chen

IJCAI 2016 Transfer Learning with Active Queries from Source Domain Sheng-Jun Huang, Songcan Chen

IJCAI 2015 Multi-Label Active Learning: Query Type Matters Sheng-Jun Huang, Songcan Chen, Zhi-Hua Zhou

AAAI 2014 Fast Multi-Instance Multi-Label Learning Sheng-Jun Huang, Wei Gao, Zhi-Hua Zhou

AAAI 2012 Multi-Label Learning by Exploiting Label Correlations Locally Sheng-Jun Huang, Zhi-Hua Zhou

NeurIPS 2010 Active Learning by Querying Informative and Representative Examples Sheng-jun Huang, Rong Jin, Zhi-Hua Zhou