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Publication search results
found 26 matches
- 2024
- Wojciech Rejchel, Pawel Teisseyre, Jan Mielniczuk:
Joint empirical risk minimization for instance-dependent positive-unlabeled data. Knowl. Based Syst. 304: 112444 (2024) - 2023
- Junwei Gu, Yu Wang, Guochao Wang:
Multi-Instance Adversarial Learning Domain Adaptation Network for Failure Prediction of Unlabeled Solid-State Drives. IEEE Trans. Instrum. Meas. 72: 1-11 (2023) - Lei Feng, Senlin Shu, Yuzhou Cao, Lue Tao, Hongxin Wei, Tao Xiang, Bo An, Gang Niu:
Multiple-Instance Learning From Unlabeled Bags With Pairwise Similarity. IEEE Trans. Knowl. Data Eng. 35(11): 11599-11609 (2023) - Lorenzo Perini, Vincent Vercruyssen, Jesse Davis:
Learning from Positive and Unlabeled Multi-Instance Bags in Anomaly Detection. KDD 2023: 1897-1906 - Wojciech Rejchel, Pawel Teisseyre, Jan Mielniczuk:
Joint empirical risk minimization for instance-dependent positive-unlabeled data. CoRR abs/2312.16557 (2023) - 2022
- Cephas A. S. Barreto, Arthur Costa Gorgônio, João C. Xavier Junior, Anne Magály de Paula Canuto:
Applying Efficient Selection Techniques of Unlabeled Instances for Wrapper-Based Semi-Supervised Methods. IEEE Access 10: 43535-43551 (2022) - Xijia Tang, Chao Xu, Tingjin Luo, Chenping Hou:
Multi-instance positive and unlabeled learning with bi-level embedding. Intell. Data Anal. 26(3): 659-678 (2022) - Chen Gong, Qizhou Wang, Tongliang Liu, Bo Han, Jane You, Jian Yang, Dacheng Tao:
Instance-Dependent Positive and Unlabeled Learning With Labeling Bias Estimation. IEEE Trans. Pattern Anal. Mach. Intell. 44(8): 4163-4177 (2022) - Yikai Wang, Li Zhang, Yuan Yao, Yanwei Fu:
How to Trust Unlabeled Data? Instance Credibility Inference for Few-Shot Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6240-6253 (2022) - Carlos Ortega Vázquez, Jochen De Weerdt, Seppe vanden Broucke:
The Hidden Cost of Fraud: An Instance-Dependent Cost-Sensitive Approach for Positive and Unlabeled Learning. LIDTA 2022: 53-67 - Leander Lauenburg, Zudi Lin, Ruihan Zhang, Márcia dos Santos, Siyu Huang, Ignacio Arganda-Carreras, Edward S. Boyden, Hanspeter Pfister, Donglai Wei:
Instance Segmentation of Unlabeled Modalities via Cyclic Segmentation GAN. CoRR abs/2204.03082 (2022) - 2021
- Guochao Wang, Yu Wang, Xiaojie Sun:
Multi-Instance Deep Learning Based on Attention Mechanism for Failure Prediction of Unlabeled Hard Disk Drives. IEEE Trans. Instrum. Meas. 70: 1-9 (2021) - Yu Li, Min Li, Qiuxia Lai, Yannan Liu, Qiang Xu:
TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks. NeurIPS 2021: 20874-20886 - Yu Li, Min Li, Qiuxia Lai, Yannan Liu, Qiang Xu:
TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks. CoRR abs/2105.10113 (2021) - 2020
- Yamin Han, Peng Zhang, Wei Huang, Yufei Zha, Garth Douglas Cooper, Yanning Zhang:
Robust Visual Tracking based on Adversarial Unlabeled Instance Generation with Label Smoothing Loss Regularization. Pattern Recognit. 97 (2020) - Tomer Grossman, Ilan Komargodski, Moni Naor:
Instance Complexity and Unlabeled Certificates in the Decision Tree Model. ITCS 2020: 56:1-56:38 - Yikai Wang, Li Zhang, Yuan Yao, Yanwei Fu:
How to trust unlabeled data? Instance Credibility Inference for Few-Shot Learning. CoRR abs/2007.08461 (2020) - 2019
- Tomer Grossman, Ilan Komargodski, Moni Naor:
Instance Complexity and Unlabeled Certificates in the Decision Tree Model. Electron. Colloquium Comput. Complex. TR19 (2019) - 2018
- Han Bao, Tomoya Sakai, Issei Sato, Masashi Sugiyama:
Convex formulation of multiple instance learning from positive and unlabeled bags. Neural Networks 105: 132-141 (2018) - 2017
- Youngjun Kim, Ellen Riloff, Stéphane M. Meystre:
Exploiting Unlabeled Texts with Clustering-based Instance Selection for Medical Relation Classification. AMIA 2017 - Han Bao, Tomoya Sakai, Issei Sato, Masashi Sugiyama:
Risk Minimization Framework for Multiple Instance Learning from Positive and Unlabeled Bags. CoRR abs/1704.06767 (2017) - 2014
- Jia Wu, Xingquan Zhu, Chengqi Zhang, Zhihua Cai:
Multi-Instance Learning from Positive and Unlabeled Bags. PAKDD (1) 2014: 237-248 - 2012
- Liangxiao Jiang:
Learning Instance Weighted Naive Bayes from labeled and unlabeled data. J. Intell. Inf. Syst. 38(1): 257-268 (2012) - 2011
- Yufeng Li, Zhi-Hua Zhou:
Improving Semi-Supervised Support Vector Machines Through Unlabeled Instances Selection. AAAI 2011: 386-391 - 2010
- Hanen Borchani, Pedro Larrañaga, Concha Bielza:
Mining Concept-Drifting Data Streams Containing Labeled and Unlabeled Instances. IEA/AIE (1) 2010: 531-540 - 2008
- Jun Long, Jianping Yin, En Zhu, Wentao Zhao:
Active Learning with Misclassification Sampling Using Diverse Ensembles Enhanced by Unlabeled Instances. PAKDD 2008: 951-957
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