Gang Niu
- Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels
2018/04/18 by Bo Han, Quanming Yao, Han, Bo +13 · 73 citations
Computer Science · #FOS: Computer and information sciences #Imbalanced Data Classification Techniques #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
- Positive-Unlabeled Learning with Non-Negative Risk Estimator
2017/03/02 by Ryuichi Kiryo, Kiryo, Ryuichi, Gang Niu +5 · 34 citations
Computer Science · #Machine Learning and Data Classification #Machine Learning and Algorithms #Domain Adaptation and Few-Shot Learning
- How does Disagreement Help Generalization against Label Corruption?
2019/01/14 by Xingrui Yu, Yu, Xingrui, Bo Han +9 · 41 citations
Computer Science · #Machine Learning and Data Classification #Imbalanced Data Classification Techniques #Machine Learning and Algorithms
- Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations
2021/10/22 by Jiaheng Wei, Wei, Jiaheng, Zhaowei Zhu +9 · 28 citations
Computer Science · #FOS: Computer and information sciences #Imbalanced Data Classification Techniques #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
- Are Anchor Points Really Indispensable in Label-Noise Learning?
2019/06/01 by Xiaobo Xia, Tongliang Liu, Xia, Xiaobo +11 · 14 citations
Computer Science · #Machine Learning and Data Classification #Machine Learning and Algorithms #Advanced Multi-Objective Optimization Algorithms
- Rethinking Importance Weighting for Deep Learning under Distribution Shift
2020/06/08 by Tongtong Fang, Fang, Tongtong, Nan Lu +5 · 13 citations
Computer Science · #Anomaly Detection Techniques and Applications #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Machine Learning and ELM
- Understanding and Improving Early Stopping for Learning with Noisy Labels
2021/06/30 by Yingbin Bai, Bai, Yingbin, Erkun Yang +13 · 12 citations
Computer Science · Engineering · #Machine Learning and Data Classification #Industrial Vision Systems and Defect Detection #Advanced Neural Network Applications
- Attacks Which Do Not Kill Training Make Adversarial Learning Stronger
2020/02/26 by Jingfeng Zhang, Xilie Xu, Zhang, Jingfeng +11 · 15 citations
Computer Science · #Adversarial Robustness in Machine Learning #Domain Adaptation and Few-Shot Learning #Anomaly Detection Techniques and Applications
- Learning from Complementary Labels
2017/05/22 by Takashi Ishida, Ishida, Takashi, Gang Niu +5 · 9 citations
Computer Science · #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
- Progressive Identification of True Labels for Partial-Label Learning
2020/02/19 by Jiaqi Lv, Lv, Jiaqi, Miao Xu +9 · 10 citations
Computer Science · Engineering · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Text and Document Classification Technologies #Water Systems and Optimization
- Provably Consistent Partial-Label Learning
2020/07/17 by Lei Feng, Jiaqi Lv, Feng, Lei +13 · 9 citations
Computer Science · #Text and Document Classification Technologies #Machine Learning and Data Classification #Machine Learning and Algorithms
- Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning
2020/06/14 by Yu Yao, Tongliang Liu, Yao, Yu +11 · 9 citations
Computer Science · Engineering · #Machine Learning and Data Classification #Advanced Multi-Objective Optimization Algorithms #Industrial Vision Systems and Defect Detection
- On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data
2018/08/31 by Nan Lu, Lu, Nan, Gang Niu +5 · 7 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
- Do We Need Zero Training Loss After Achieving Zero Training Error?
2020/02/20 by Takashi Ishida, Ishida, Takashi, Ikko Yamane +7 · 8 citations
Computer Science · Health Professions · Psychology · #FOS: Computer and information sciences #Human Resource Development and Performance Evaluation #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Quality and Safety in Healthcare #Smart Systems and Machine Learning
- Learning with Multiple Complementary Labels
2019/12/30 by Lei Feng, Takuo Kaneko, Feng, Lei +9 · 7 citations
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification #Text and Document Classification Technologies
- Probabilistic Margins for Instance Reweighting in Adversarial Training
2021/06/15 by Qizhou Wang, Wang, Qizhou, Feng Liu +13 · 7 citations
Computer Science · Engineering · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Integrated Circuits and Semiconductor Failure Analysis
- Complementary-Label Learning for Arbitrary Losses and Models
2018/10/10 by Takashi Ishida, Gang Niu, Ishida, Takashi +5 · 6 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization
2021/02/04 by Yivan Zhang, Zhang, Yivan, Gang Niu +3 · 6 citations
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification #Neural Networks and Applications
- Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach
2019/10/20 by Nan Lu, Lu, Nan, Tianyi Zhang +5 · 5 citations
Computer Science · #Machine Learning and Data Classification #Machine Learning and Algorithms #Imbalanced Data Classification Techniques
- Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization
2024/05/29 by Ziqing Fan, Shengchao Hu, Fan, Ziqing +11 · 9 citations
Computer Science · Engineering · #Distributed #FOS: Computer and information sciences #Ferroelectric and Negative Capacitance Devices #Machine Learning (cs.LG) #Parallel #Privacy-Preserving Technologies in Data #Stochastic Gradient Optimization Techniques #and Cluster Computing (cs.DC)
- Learning from Similarity-Confidence Data
2021/02/13 by Yuzhou Cao, Lei Feng, Cao, Yuzhou +9 · 4 citations
Computer Science · #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
- Binary Classification from Positive-Confidence Data
2017/10/19 by Takashi Ishida, Gang Niu, Ishida, Takashi +3 · 3 citations
Computer Science · #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Imbalanced Data Classification Techniques #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Maximum Mean Discrepancy Test is Aware of Adversarial Attacks
2020/10/22 by Ruize Gao, Gao, Ruize, Feng Liu +11 · 4 citations
Engineering · #FOS: Computer and information sciences #Integrated Circuits and Semiconductor Failure Analysis #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Pointwise Binary Classification with Pairwise Confidence Comparisons
2020/10/05 by Lei Feng, Senlin Shu, Feng, Lei +13 · 3 citations
Computer Science · #FOS: Computer and information sciences #Imbalanced Data Classification Techniques #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
- Mitigating Memorization of Noisy Labels by Clipping the Model Prediction
2022/12/08 by Hongxin Wei, Huiping Zhuang, Wei, Hongxin +11 · 4 citations
Computer Science · #Machine Learning and Data Classification #Neural Networks and Applications #Music and Audio Processing
- On the Effectiveness of Adversarial Training against Backdoor Attacks
2022/02/22 by Ying-Hua Gao, Dongxian Wu, Gao, Yinghua +11 · 3 citations
Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation
2023/10/21 by Jianing Zhu, Zhu, Jianing, Yu Geng +11 · 4 citations
Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification
- Masking: A New Perspective of Noisy Supervision
2018/05/21 by Bo Han, Jiangchao Yao, Han, Bo +11 · 2 citations
Computer Science · Engineering · #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Water Systems and Optimization
- Unbiased Risk Estimators Can Mislead: A Case Study of Learning with\n Complementary Labels
2020/07/05 by Yu-Ting Chou, Chou, Yu-Ting, Gang Niu +5 · 5 citations
Computer Science · #Anomaly Detection Techniques and Applications #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
- Instance-dependent Label-noise Learning under a Structural Causal Model
2021/09/07 by Yu Yao, Yao, Yu, Tongliang Liu +9 · 2 citations
Computer Science · #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
- Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data
2016/05/23 by Tomoya Sakai, Sakai, Tomoya, Marthinus Christoffel du Plessis +5 · 2 citations
Computer Science · Mathematics · #Advanced Statistical Methods and Models #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and Data Classification
- A Universal Unbiased Method for Classification from Aggregate Observations
2023/06/20 by Zixi Wei, Lei Feng, Wei, Zixi +11 · 2 citations
Computer Science · #Machine Learning and Data Classification #Imbalanced Data Classification Techniques #Data Mining Algorithms and Applications
- Direct Distillation between Different Domains
2024/01/12 by Jialiang Tang, Tang, Jialiang, Shuo Chen +11 · 2 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #Multimodal Machine Learning Applications #Machine Learning and ELM
- Fairness Improves Learning from Noisily Labeled Long-Tailed Data
2023/03/22 by Jiaheng Wei, Zhaowei Zhu, Wei, Jiaheng +11 · 2 citations
Computer Science · #Machine Learning and Data Classification
- Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition under Reshuffling
2018/05/22 by Chao Li, Li, Chao, Mohammad Emtiyaz Khan +11 · 1 citation
Mathematics · Engineering · Medicine · #Tensor decomposition and applications #Sparse and Compressive Sensing Techniques #Advanced Neuroimaging Techniques and Applications
- Accurate Forgetting for Heterogeneous Federated Continual Learning
2025/02/20 by Abudukelimu Wuerkaixi, Sen Cui, Wuerkaixi, Abudukelimu +15 · 4 citations
Computer Science · Engineering · #Artificial Intelligence (cs.AI) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Geophysical Methods and Applications #Machine Learning (cs.LG)
- Class-Distribution-Aware Pseudo Labeling for Semi-Supervised Multi-Label Learning
2023/05/04 by Mingkun Xie, Jia‐Hao Xiao, Xie, Ming-Kun +8 · 2 citations
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Text and Document Classification Technologies
- CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection
2021/02/10 by Hanshu Yan, Jingfeng Zhang, Yan, Hanshu +9 · 1 citation
Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification
2022/02/01 by Takashi Ishida, Ishida, Takashi, Ikko Yamane +7 · 1 citation
Computer Science · Health Professions · #Artificial Intelligence in Healthcare #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack
2022/06/15 by Ruize Gao, Gao, Ruize, Jiongxiao Wang +13 · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · #Adversarial Robustness in Machine Learning #Bacillus and Francisella bacterial research #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Instance-Dependent Label-Noise Learning with Manifold-Regularized Transition Matrix Estimation
2022/06/06 by De Cheng, Tongliang Liu, Cheng, De +13 · 1 citation
Computer Science · #Machine Learning and Data Classification #Advanced Multi-Objective Optimization Algorithms #Music and Audio Processing
- Realistic Evaluation of Deep Partial-Label Learning Algorithms
2025/02/14 by Wei Wang, Wang, Wei, Dongdong Wu +9 · 5 citations
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Rough Sets and Fuzzy Logic #Text and Document Classification Technologies #Web Applications and Data Management
- Distribution Shift Matters for Knowledge Distillation with Webly Collected Images
2023/07/21 by Jialiang Tang, Shuo Chen, Tang, Jialiang +7 · 1 citation
Computer Science · #AI in cancer detection #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis
- Understanding the Interaction of Adversarial Training with Noisy Labels
2021/02/06 by Jianing Zhu, Zhu, Jianing, Jingfeng Zhang +13 · 1 citation
Computer Science · #Adversarial Robustness in Machine Learning #Machine Learning and Data Classification #Machine Learning and Algorithms
- Balancing Similarity and Complementarity for Federated Learning
2024/05/16 by Kunda Yan, Yan, Kunda, Sen Cui +13 · 1 citation
Computer Science · #Distributed #FOS: Computer and information sciences #Machine Learning (cs.LG) #Parallel #Privacy-Preserving Technologies in Data #and Cluster Computing (cs.DC)
- Decoupling the Class Label and the Target Concept in Machine Unlearning
2024/06/12 by Jianing Zhu, Bo Han, Zhu, Jianing +9 · 1 citation
Computer Science · Engineering · #Educational Technology and Assessment #Engineering Education and Curriculum Development #FOS: Computer and information sciences #Machine Learning (cs.LG) #Online Learning and Analytics
- Learning without Isolation: Pathway Protection for Continual Learning
2025/05/24 by Zhikang Chen, Chen, Zhikang, Abudukelimu Wuerkaixi +22 · 2 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms