Статті в журналах з теми "Learning with noisy labels"
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Xie, Ming-Kun, and Sheng-Jun Huang. "Partial Multi-Label Learning with Noisy Label Identification." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 6454–61. http://dx.doi.org/10.1609/aaai.v34i04.6117.
Повний текст джерелаChen, Mingcai, Hao Cheng, Yuntao Du, Ming Xu, Wenyu Jiang, and Chongjun Wang. "Two Wrongs Don’t Make a Right: Combating Confirmation Bias in Learning with Label Noise." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 12 (June 26, 2023): 14765–73. http://dx.doi.org/10.1609/aaai.v37i12.26725.
Повний текст джерелаLi, Hui, Zhaodong Niu, Quan Sun, and Yabo Li. "Co-Correcting: Combat Noisy Labels in Space Debris Detection." Remote Sensing 14, no. 20 (October 21, 2022): 5261. http://dx.doi.org/10.3390/rs14205261.
Повний текст джерелаTang, Xinyu, Milad Nasr, Saeed Mahloujifar, Virat Shejwalkar, Liwei Song, Amir Houmansadr, and Prateek Mittal. "Machine Learning with Differentially Private Labels: Mechanisms and Frameworks." Proceedings on Privacy Enhancing Technologies 2022, no. 4 (October 2022): 332–50. http://dx.doi.org/10.56553/popets-2022-0112.
Повний текст джерелаWu, Yichen, Jun Shu, Qi Xie, Qian Zhao, and Deyu Meng. "Learning to Purify Noisy Labels via Meta Soft Label Corrector." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 12 (May 18, 2021): 10388–96. http://dx.doi.org/10.1609/aaai.v35i12.17244.
Повний текст джерелаZheng, Guoqing, Ahmed Hassan Awadallah, and Susan Dumais. "Meta Label Correction for Noisy Label Learning." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 12 (May 18, 2021): 11053–61. http://dx.doi.org/10.1609/aaai.v35i12.17319.
Повний текст джерелаShi, Jialin, Chenyi Guo, and Ji Wu. "A Hybrid Robust-Learning Architecture for Medical Image Segmentation with Noisy Labels." Future Internet 14, no. 2 (January 26, 2022): 41. http://dx.doi.org/10.3390/fi14020041.
Повний текст джерелаNorthcutt, Curtis, Lu Jiang, and Isaac Chuang. "Confident Learning: Estimating Uncertainty in Dataset Labels." Journal of Artificial Intelligence Research 70 (April 14, 2021): 1373–411. http://dx.doi.org/10.1613/jair.1.12125.
Повний текст джерелаSilva, Amila, Ling Luo, Shanika Karunasekera, and Christopher Leckie. "Noise-Robust Learning from Multiple Unsupervised Sources of Inferred Labels." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 8 (June 28, 2022): 8315–23. http://dx.doi.org/10.1609/aaai.v36i8.20806.
Повний текст джерелаYan, Xuguo, Xuhui Xia, Lei Wang, and Zelin Zhang. "A Progressive Deep Neural Network Training Method for Image Classification with Noisy Labels." Applied Sciences 12, no. 24 (December 12, 2022): 12754. http://dx.doi.org/10.3390/app122412754.
Повний текст джерелаLi, Shikun, Shiming Ge, Yingying Hua, Chunhui Zhang, Hao Wen, Tengfei Liu, and Weiqiang Wang. "Coupled-View Deep Classifier Learning from Multiple Noisy Annotators." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 4667–74. http://dx.doi.org/10.1609/aaai.v34i04.5898.
Повний текст джерелаChen, Pengfei, Junjie Ye, Guangyong Chen, Jingwei Zhao, and Pheng-Ann Heng. "Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 13 (May 18, 2021): 11451–61. http://dx.doi.org/10.1609/aaai.v35i13.17364.
Повний текст джерелаYi, Rumeng, Dayan Guan, Yaping Huang, and Shijian Lu. "Class-Independent Regularization for Learning with Noisy Labels." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 3 (June 26, 2023): 3276–84. http://dx.doi.org/10.1609/aaai.v37i3.25434.
Повний текст джерелаGuo, Biyang, Songqiao Han, Xiao Han, Hailiang Huang, and Ting Lu. "Label Confusion Learning to Enhance Text Classification Models." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 14 (May 18, 2021): 12929–36. http://dx.doi.org/10.1609/aaai.v35i14.17529.
Повний текст джерелаNushi, Besmira, Adish Singla, Andreas Krause, and Donald Kossmann. "Learning and Feature Selection under Budget Constraints in Crowdsourcing." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 4 (September 21, 2016): 159–68. http://dx.doi.org/10.1609/hcomp.v4i1.13278.
Повний текст джерелаKo, Jongwoo, Bongsoo Yi, and Se-Young Yun. "A Gift from Label Smoothing: Robust Training with Adaptive Label Smoothing via Auxiliary Classifier under Label Noise." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 7 (June 26, 2023): 8325–33. http://dx.doi.org/10.1609/aaai.v37i7.26004.
Повний текст джерелаZhao, Tianna, Yuanjian Zhang, and Witold Pedrycz. "Robust Multi-Label Classification with Enhanced Global and Local Label Correlation." Mathematics 10, no. 11 (May 30, 2022): 1871. http://dx.doi.org/10.3390/math10111871.
Повний текст джерелаNie, Binling, and Chenyang Li. "Distantly Supervised Named Entity Recognition with Self-Adaptive Label Correction." Applied Sciences 12, no. 15 (July 29, 2022): 7659. http://dx.doi.org/10.3390/app12157659.
Повний текст джерелаZhang, Minxue, Ning Xu, and Xin Geng. "Feature-Induced Label Distribution for Learning with Noisy Labels." Pattern Recognition Letters 155 (March 2022): 107–13. http://dx.doi.org/10.1016/j.patrec.2022.02.011.
Повний текст джерелаLi, Guozheng, Peng Wang, Qiqing Luo, Yanhe Liu, and Wenjun Ke. "Online Noisy Continual Relation Learning." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 11 (June 26, 2023): 13059–66. http://dx.doi.org/10.1609/aaai.v37i11.26534.
Повний текст джерелаYan, Shaotian, Xiang Tian, Rongxin Jiang, and Yaowu Chen. "FGCM: Noisy Label Learning via Fine-Grained Confidence Modeling." Applied Sciences 12, no. 22 (November 10, 2022): 11406. http://dx.doi.org/10.3390/app122211406.
Повний текст джерелаWang, Zixiao, Junwu Weng, Chun Yuan, and Jue Wang. "Truncate-Split-Contrast: A Framework for Learning from Mislabeled Videos." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 3 (June 26, 2023): 2751–58. http://dx.doi.org/10.1609/aaai.v37i3.25375.
Повний текст джерелаWang, Deng-Bao, Yong Wen, Lujia Pan, and Min-Ling Zhang. "Learning from Noisy Labels with Complementary Loss Functions." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 11 (May 18, 2021): 10111–19. http://dx.doi.org/10.1609/aaai.v35i11.17213.
Повний текст джерелаLiu, Xiaoli, Baoping Tang, Qikang Li, and Qichao Yang. "Twin prototype networks with noisy label self-correction for fault diagnosis of wind turbine gearboxes." Measurement Science and Technology 34, no. 3 (December 1, 2022): 035006. http://dx.doi.org/10.1088/1361-6501/aca3c3.
Повний текст джерелаDuan, Yunyan, and Ou Wu. "Learning With Auxiliary Less-Noisy Labels." IEEE Transactions on Neural Networks and Learning Systems 28, no. 7 (July 2017): 1716–21. http://dx.doi.org/10.1109/tnnls.2016.2546956.
Повний текст джерелаHan, Bo, Ivor W. Tsang, Ling Chen, Celina P. Yu, and Sai-Fu Fung. "Progressive Stochastic Learning for Noisy Labels." IEEE Transactions on Neural Networks and Learning Systems 29, no. 10 (October 2018): 5136–48. http://dx.doi.org/10.1109/tnnls.2018.2792062.
Повний текст джерелаZhao, Pan, Long Tang, and Zhigeng Pan. "Zero-Shot Learning with Noisy Labels." Procedia Computer Science 221 (2023): 763–72. http://dx.doi.org/10.1016/j.procs.2023.08.049.
Повний текст джерелаXu, Ran, Yue Yu, Hejie Cui, Xuan Kan, Yanqiao Zhu, Joyce Ho, Chao Zhang, and Carl Yang. "Neighborhood-Regularized Self-Training for Learning with Few Labels." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 9 (June 26, 2023): 10611–19. http://dx.doi.org/10.1609/aaai.v37i9.26260.
Повний текст джерелаJian, Ling, Fuhao Gao, Peng Ren, Yunquan Song, and Shihua Luo. "A Noise-Resilient Online Learning Algorithm for Scene Classification." Remote Sensing 10, no. 11 (November 20, 2018): 1836. http://dx.doi.org/10.3390/rs10111836.
Повний текст джерелаZhang, Youqiang, Jin Sun, Hao Shi, Zixian Ge, Qiqiong Yu, Guo Cao, and Xuesong Li. "Agreement and Disagreement-Based Co-Learning with Dual Network for Hyperspectral Image Classification with Noisy Labels." Remote Sensing 15, no. 10 (May 12, 2023): 2543. http://dx.doi.org/10.3390/rs15102543.
Повний текст джерелаZhang, Yaojie, Huahu Xu, Junsheng Xiao, and Minjie Bian. "JoSDW: Combating Noisy Labels by Dynamic Weight." Future Internet 14, no. 2 (February 2, 2022): 50. http://dx.doi.org/10.3390/fi14020050.
Повний текст джерелаChen, Mingxia, Jing Wang, Xueqing Li, and Xiaolong Sun. "Robust Semi-Supervised Manifold Learning Algorithm for Classification." Mathematical Problems in Engineering 2018 (2018): 1–8. http://dx.doi.org/10.1155/2018/2382803.
Повний текст джерелаLi, Weiwei, Yuqing Lu, Lei Chen, and Xiuyi Jia. "Label distribution learning with noisy labels via three-way decisions." International Journal of Approximate Reasoning 150 (November 2022): 19–34. http://dx.doi.org/10.1016/j.ijar.2022.08.009.
Повний текст джерелаLong, Lingli, Yongjin Zhu, Jun Shao, Zheng Kong, Jian Li, Yanzheng Xiang, and Xu Zhang. "NL2SQL Generation with Noise Labels based on Multi-task Learning." Journal of Physics: Conference Series 2294, no. 1 (June 1, 2022): 012016. http://dx.doi.org/10.1088/1742-6596/2294/1/012016.
Повний текст джерелаYan, Yan, and Yuhong Guo. "Partial Label Learning with Batch Label Correction." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 6575–82. http://dx.doi.org/10.1609/aaai.v34i04.6132.
Повний текст джерелаKong, Kyeongbo, Junggi Lee, Youngchul Kwak, Young-Rae Cho, Seong-Eun Kim, and Woo-Jin Song. "Penalty based robust learning with noisy labels." Neurocomputing 489 (June 2022): 112–27. http://dx.doi.org/10.1016/j.neucom.2022.02.030.
Повний текст джерелаSun, Yi, Yan Tian, Yiping Xu, and Jianxiang Li. "Limited Gradient Descent: Learning With Noisy Labels." IEEE Access 7 (2019): 168296–306. http://dx.doi.org/10.1109/access.2019.2954547.
Повний текст джерелаSun, Haoliang, Chenhui Guo, Qi Wei, Zhongyi Han, and Yilong Yin. "Learning to rectify for robust learning with noisy labels." Pattern Recognition 124 (April 2022): 108467. http://dx.doi.org/10.1016/j.patcog.2021.108467.
Повний текст джерелаLin, Chuang, Shanxin Guo, Jinsong Chen, Luyi Sun, Xiaorou Zheng, Yan Yang, and Yingfei Xiong. "Deep Learning Network Intensification for Preventing Noisy-Labeled Samples for Remote Sensing Classification." Remote Sensing 13, no. 9 (April 27, 2021): 1689. http://dx.doi.org/10.3390/rs13091689.
Повний текст джерелаZhao, QiHao, Wei Hu, Yangyu Huang, and Fan Zhang. "P-DIFF+: Improving learning classifier with noisy labels by Noisy Negative Learning loss." Neural Networks 144 (December 2021): 1–10. http://dx.doi.org/10.1016/j.neunet.2021.07.024.
Повний текст джерелаXu, Ning, Yun-Peng Liu, and Xin Geng. "Partial Multi-Label Learning with Label Distribution." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 6510–17. http://dx.doi.org/10.1609/aaai.v34i04.6124.
Повний текст джерелаYao, Jiangchao, Hao Wu, Ya Zhang, Ivor W. Tsang, and Jun Sun. "Safeguarded Dynamic Label Regression for Noisy Supervision." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 9103–10. http://dx.doi.org/10.1609/aaai.v33i01.33019103.
Повний текст джерелаSun, Lijuan, Ping Ye, Gengyu Lyu, Songhe Feng, Guojun Dai, and Hua Zhang. "Weakly-supervised multi-label learning with noisy features and incomplete labels." Neurocomputing 413 (November 2020): 61–71. http://dx.doi.org/10.1016/j.neucom.2020.06.101.
Повний текст джерелаLiu, Kun-Lin, Wu-Jun Li, and Minyi Guo. "Emoticon Smoothed Language Models for Twitter Sentiment Analysis." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (September 20, 2021): 1678–84. http://dx.doi.org/10.1609/aaai.v26i1.8353.
Повний текст джерелаBüttner, Martha, Lisa Schneider, Aleksander Krasowski, Joachim Krois, Ben Feldberg, and Falk Schwendicke. "Impact of Noisy Labels on Dental Deep Learning—Calculus Detection on Bitewing Radiographs." Journal of Clinical Medicine 12, no. 9 (April 23, 2023): 3058. http://dx.doi.org/10.3390/jcm12093058.
Повний текст джерелаZhang, Qian, Feifei Lee, Ya-gang Wang, Ran Miao, Lei Chen, and Qiu Chen. "An improved noise loss correction algorithm for learning from noisy labels." Journal of Visual Communication and Image Representation 72 (October 2020): 102930. http://dx.doi.org/10.1016/j.jvcir.2020.102930.
Повний текст джерелаZhao, Yue, Guoqing Zheng, Subhabrata Mukherjee, Robert McCann, and Ahmed Awadallah. "ADMoE: Anomaly Detection with Mixture-of-Experts from Noisy Labels." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 4 (June 26, 2023): 4937–45. http://dx.doi.org/10.1609/aaai.v37i4.25620.
Повний текст джерелаLuo, Yaoru, Guole Liu, Yuanhao Guo, and Ge Yang. "Deep Neural Networks Learn Meta-Structures from Noisy Labels in Semantic Segmentation." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 2 (June 28, 2022): 1908–16. http://dx.doi.org/10.1609/aaai.v36i2.20085.
Повний текст джерелаZheng, Kecheng, Cuiling Lan, Wenjun Zeng, Zhizheng Zhang, and Zheng-Jun Zha. "Exploiting Sample Uncertainty for Domain Adaptive Person Re-Identification." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 4 (May 18, 2021): 3538–46. http://dx.doi.org/10.1609/aaai.v35i4.16468.
Повний текст джерелаWang, Ziyang, and Irina Voiculescu. "Dealing with Unreliable Annotations: A Noise-Robust Network for Semantic Segmentation through A Transformer-Improved Encoder and Convolution Decoder." Applied Sciences 13, no. 13 (July 7, 2023): 7966. http://dx.doi.org/10.3390/app13137966.
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