Artículos de revistas sobre el tema "Maximum Mean Discrepancy (MMD)"
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Huang, Qihang, Yulin He y Zhexue Huang. "A Novel Maximum Mean Discrepancy-Based Semi-Supervised Learning Algorithm". Mathematics 10, n.º 1 (23 de diciembre de 2021): 39. http://dx.doi.org/10.3390/math10010039.
Texto completoZhou, Zhaokun, Yuanhong Zhong, Xiaoming Liu, Qiang Li y Shu Han. "DC-MMD-GAN: A New Maximum Mean Discrepancy Generative Adversarial Network Using Divide and Conquer". Applied Sciences 10, n.º 18 (14 de septiembre de 2020): 6405. http://dx.doi.org/10.3390/app10186405.
Texto completoXu, Haoji. "Generate Faces Using Ladder Variational Autoencoder with Maximum Mean Discrepancy (MMD)". Intelligent Information Management 10, n.º 04 (2018): 108–13. http://dx.doi.org/10.4236/iim.2018.104009.
Texto completoSun, Jiancheng. "Complex Network Construction of Univariate Chaotic Time Series Based on Maximum Mean Discrepancy". Entropy 22, n.º 2 (24 de enero de 2020): 142. http://dx.doi.org/10.3390/e22020142.
Texto completoZhang, Xiangqing, Yan Feng, Shun Zhang, Nan Wang, Shaohui Mei y Mingyi He. "Semi-Supervised Person Detection in Aerial Images with Instance Segmentation and Maximum Mean Discrepancy Distance". Remote Sensing 15, n.º 11 (4 de junio de 2023): 2928. http://dx.doi.org/10.3390/rs15112928.
Texto completoZhao, Ji y Deyu Meng. "FastMMD: Ensemble of Circular Discrepancy for Efficient Two-Sample Test". Neural Computation 27, n.º 6 (junio de 2015): 1345–72. http://dx.doi.org/10.1162/neco_a_00732.
Texto completoWilliamson, Sinead A. y Jette Henderson. "Understanding Collections of Related Datasets Using Dependent MMD Coresets". Information 12, n.º 10 (23 de septiembre de 2021): 392. http://dx.doi.org/10.3390/info12100392.
Texto completoLi, Kangji, Borui Wei, Qianqian Tang y Yufei Liu. "A Data-Efficient Building Electricity Load Forecasting Method Based on Maximum Mean Discrepancy and Improved TrAdaBoost Algorithm". Energies 15, n.º 23 (22 de noviembre de 2022): 8780. http://dx.doi.org/10.3390/en15238780.
Texto completoLee, Junghyun, Gwangsu Kim, Mahbod Olfat, Mark Hasegawa-Johnson y Chang D. Yoo. "Fast and Efficient MMD-Based Fair PCA via Optimization over Stiefel Manifold". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 7 (28 de junio de 2022): 7363–71. http://dx.doi.org/10.1609/aaai.v36i7.20699.
Texto completoHan, Chao, Deyun Zhou, Zhen Yang, Yu Xie y Kai Zhang. "Discriminative Sparse Filtering for Multi-Source Image Classification". Sensors 20, n.º 20 (16 de octubre de 2020): 5868. http://dx.doi.org/10.3390/s20205868.
Texto completoSong, Mengmeng, Zexiong Zhang, Shungen Xiao, Zicheng Xiong y Mengwei Li. "Bearing fault diagnosis method using a spatio-temporal neural network based on feature transfer learning". Measurement Science and Technology 34, n.º 1 (25 de octubre de 2022): 015119. http://dx.doi.org/10.1088/1361-6501/ac9078.
Texto completoWang, Jinrui, Shanshan Ji, Baokun Han, Huaiqian Bao y Xingxing Jiang. "Deep Adaptive Adversarial Network-Based Method for Mechanical Fault Diagnosis under Different Working Conditions". Complexity 2020 (23 de julio de 2020): 1–11. http://dx.doi.org/10.1155/2020/6946702.
Texto completoWang, Haoyu, Yuhu Cheng y Xuesong Wang. "A Novel Hyperspectral Image Classification Method Using Class-Weighted Domain Adaptation Network". Remote Sensing 15, n.º 4 (10 de febrero de 2023): 999. http://dx.doi.org/10.3390/rs15040999.
Texto completoLiu, Yi, Hang Xiang, Zhansi Jiang y Jiawei Xiang. "A Domain Adaption ResNet Model to Detect Faults in Roller Bearings Using Vibro-Acoustic Data". Sensors 23, n.º 6 (13 de marzo de 2023): 3068. http://dx.doi.org/10.3390/s23063068.
Texto completoXiao, Li, Qi Chen, Shuping Hou, Zhi Yan y Yiming Tian. "Detection of an Incipient Fault for Dual Three-Phase PMSMs Using a Modified Autoencoder". Electronics 11, n.º 22 (15 de noviembre de 2022): 3741. http://dx.doi.org/10.3390/electronics11223741.
Texto completoFutami, Futoshi, Zhenghang Cui, Issei Sato y Masashi Sugiyama. "Bayesian Posterior Approximation via Greedy Particle Optimization". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julio de 2019): 3606–13. http://dx.doi.org/10.1609/aaai.v33i01.33013606.
Texto completoDu, Yuntao, Ruiting Zhang, Xiaowen Zhang, Yirong Yao, Hengyang Lu y Chongjun Wang. "Learning transferable and discriminative features for unsupervised domain adaptation". Intelligent Data Analysis 26, n.º 2 (14 de marzo de 2022): 407–25. http://dx.doi.org/10.3233/ida-215813.
Texto completoWang, Z., T. Li, L. Pan y Z. Kang. "SCENE SEMANTIC SEGMENTATION FROM INDOOR RGB-D IMAGES USING ENCODE-DECODER FULLY CONVOLUTIONAL NETWORKS". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (12 de septiembre de 2017): 397–404. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-397-2017.
Texto completoCheng, Xiuyuan, Alexander Cloninger y Ronald R. Coifman. "Two-sample statistics based on anisotropic kernels". Information and Inference: A Journal of the IMA 9, n.º 3 (10 de diciembre de 2019): 677–719. http://dx.doi.org/10.1093/imaiai/iaz018.
Texto completoChen, Chao, Zhihang Fu, Zhihong Chen, Sheng Jin, Zhaowei Cheng, Xinyu Jin y Xian-sheng Hua. "HoMM: Higher-Order Moment Matching for Unsupervised Domain Adaptation". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 3422–29. http://dx.doi.org/10.1609/aaai.v34i04.5745.
Texto completoLiu, Jian y Liming Feng. "Diversity Evolutionary Policy Deep Reinforcement Learning". Computational Intelligence and Neuroscience 2021 (3 de agosto de 2021): 1–11. http://dx.doi.org/10.1155/2021/5300189.
Texto completoTahmoresnezhad, Jafar y Sattar Hashemi. "An Efficient yet Effective Random Partitioning and Feature Weighting Approach for Transfer Learning". International Journal of Pattern Recognition and Artificial Intelligence 30, n.º 02 (febrero de 2016): 1651003. http://dx.doi.org/10.1142/s0218001416510034.
Texto completoTay, Sebastian Shenghong, Xinyi Xu, Chuan Sheng Foo y Bryan Kian Hsiang Low. "Incentivizing Collaboration in Machine Learning via Synthetic Data Rewards". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 9 (28 de junio de 2022): 9448–56. http://dx.doi.org/10.1609/aaai.v36i9.21177.
Texto completoZhang, Quanling, Ningze Tang, Xing Fu, Hao Peng, Cuimei Bo y Cunsong Wang. "A Multi-Scale Attention Mechanism Based Domain Adversarial Neural Network Strategy for Bearing Fault Diagnosis". Actuators 12, n.º 5 (27 de abril de 2023): 188. http://dx.doi.org/10.3390/act12050188.
Texto completoXu, Kun, Shunming Li, Ranran Li, Jiantao Lu, Xianglian Li y Mengjie Zeng. "Domain Adaptation Network with Double Adversarial Mechanism for Intelligent Fault Diagnosis". Applied Sciences 11, n.º 17 (28 de agosto de 2021): 7983. http://dx.doi.org/10.3390/app11177983.
Texto completoWang, Li, Guoqiang Liu, Chao Zhang, Yu Yang y Jinhao Qiu. "FEM Simulation-Based Adversarial Domain Adaptation for Fatigue Crack Detection Using Lamb Wave". Sensors 23, n.º 4 (9 de febrero de 2023): 1943. http://dx.doi.org/10.3390/s23041943.
Texto completoYang, Bingru, Qi Li, Liang Chen, Changqing Shen y Sundararajan Natarajan. "Bearing Fault Diagnosis Based on Multilayer Domain Adaptation". Shock and Vibration 2020 (29 de septiembre de 2020): 1–11. http://dx.doi.org/10.1155/2020/8873960.
Texto completoBanerjee, Subhankar y Shayok Chakraborty. "Deterministic Mini-batch Sequencing for Training Deep Neural Networks". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 8 (18 de mayo de 2021): 6723–31. http://dx.doi.org/10.1609/aaai.v35i8.16831.
Texto completoTian, Jinghui, Dongying Han, Lifeng Xiao y Peiming Shi. "Multi-scale deep coupling convolutional neural network with heterogeneous sensor data for intelligent fault diagnosis". Journal of Intelligent & Fuzzy Systems 41, n.º 1 (11 de agosto de 2021): 2225–38. http://dx.doi.org/10.3233/jifs-210932.
Texto completoZang, Shaofei, Xinghai Li, Jianwei Ma, Yongyi Yan, Jiwei Gao y Yuan Wei. "TSTELM: Two-Stage Transfer Extreme Learning Machine for Unsupervised Domain Adaptation". Computational Intelligence and Neuroscience 2022 (18 de julio de 2022): 1–18. http://dx.doi.org/10.1155/2022/1582624.
Texto completoSun, Wei, Jie Zhou, Bintao Sun, Yuqing Zhou y Yongying Jiang. "Markov Transition Field Enhanced Deep Domain Adaptation Network for Milling Tool Condition Monitoring". Micromachines 13, n.º 6 (31 de mayo de 2022): 873. http://dx.doi.org/10.3390/mi13060873.
Texto completoDing, Renjie, Xue Li, Lanshun Nie, Jiazhen Li, Xiandong Si, Dianhui Chu, Guozhong Liu y Dechen Zhan. "Empirical Study and Improvement on Deep Transfer Learning for Human Activity Recognition". Sensors 19, n.º 1 (24 de diciembre de 2018): 57. http://dx.doi.org/10.3390/s19010057.
Texto completoWang, Kai, Wei Zhao, Aidong Xu, Peng Zeng y Shunkun Yang. "One-Dimensional Multi-Scale Domain Adaptive Network for Bearing-Fault Diagnosis under Varying Working Conditions". Sensors 20, n.º 21 (23 de octubre de 2020): 6039. http://dx.doi.org/10.3390/s20216039.
Texto completoPark, Hyo-Seok, Seong-Joong Kim, Andrew L. Stewart, Seok-Woo Son y Kyong-Hwan Seo. "Mid-Holocene Northern Hemisphere warming driven by Arctic amplification". Science Advances 5, n.º 12 (diciembre de 2019): eaax8203. http://dx.doi.org/10.1126/sciadv.aax8203.
Texto completoSun, Han, Xinyi Chen, Ling Wang, Dong Liang, Ningzhong Liu y Huiyu Zhou. "C2DAN: An Improved Deep Adaptation Network with Domain Confusion and Classifier Adaptation". Sensors 20, n.º 12 (26 de junio de 2020): 3606. http://dx.doi.org/10.3390/s20123606.
Texto completoZhang, Yongchao, Zhaohui Ren y Shihua Zhou. "A New Deep Convolutional Domain Adaptation Network for Bearing Fault Diagnosis under Different Working Conditions". Shock and Vibration 2020 (24 de julio de 2020): 1–14. http://dx.doi.org/10.1155/2020/8850976.
Texto completoZhang, Jun, Wen Yao, Xiaoqian Chen y Ling Feng. "Transferable Post-hoc Calibration on Pretrained Transformers in Noisy Text Classification". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 11 (26 de junio de 2023): 13940–48. http://dx.doi.org/10.1609/aaai.v37i11.26632.
Texto completoPaul, A., K. Vogt, F. Rottensteiner, J. Ostermann y C. Heipke. "A COMPARISON OF TWO STRATEGIES FOR AVOIDING NEGATIVE TRANSFER IN DOMAIN ADAPTATION BASED ON LOGISTIC REGRESSION". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2 (30 de mayo de 2018): 845–52. http://dx.doi.org/10.5194/isprs-archives-xlii-2-845-2018.
Texto completoLi, Zhaokui, Xiangyi Tang, Wei Li, Chuanyun Wang, Cuiwei Liu y Jinrong He. "A Two-stage Deep Domain Adaptation Method for Hyperspectral Image Classification". Remote Sensing 12, n.º 7 (25 de marzo de 2020): 1054. http://dx.doi.org/10.3390/rs12071054.
Texto completoChen, Zhihong, Taiping Yao, Kekai Sheng, Shouhong Ding, Ying Tai, Jilin Li, Feiyue Huang y Xinyu Jin. "Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 2 (18 de mayo de 2021): 1132–39. http://dx.doi.org/10.1609/aaai.v35i2.16199.
Texto completoNguyen-Tang, Thanh, Sunil Gupta y Svetha Venkatesh. "Distributional Reinforcement Learning via Moment Matching". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 10 (18 de mayo de 2021): 9144–52. http://dx.doi.org/10.1609/aaai.v35i10.17104.
Texto completoZhang, Qiyang, Zhibin Zhao, Xingwu Zhang, Yilong Liu, Xiaolei Yu y Xuefeng Chen. "Short-time consistent domain adaptation for rolling bearing fault diagnosis under varying working conditions". Measurement Science and Technology 33, n.º 7 (6 de abril de 2022): 075105. http://dx.doi.org/10.1088/1361-6501/ac5874.
Texto completoHussein, Amir y Hazem Hajj. "Domain Adaptation with Representation Learning and Nonlinear Relation for Time Series". ACM Transactions on Internet of Things 3, n.º 2 (31 de mayo de 2022): 1–26. http://dx.doi.org/10.1145/3502905.
Texto completoHe, Yiwei, Yingjie Tian, Jingjing Tang y Yue Ma. "Unsupervised Domain Adaptation Using Exemplar-SVMs with Adaptation Regularization". Complexity 2018 (2018): 1–13. http://dx.doi.org/10.1155/2018/8425821.
Texto completoZhu, Qiuyu, Liheng Hu y Rui Wang. "Image Clustering Algorithm Based on Predefined Evenly-Distributed Class Centroids and Composite Cosine Distance". Entropy 24, n.º 11 (26 de octubre de 2022): 1533. http://dx.doi.org/10.3390/e24111533.
Texto completoYe, Fei y Adrian G. Bors. "Lifelong Compression Mixture Model via Knowledge Relationship Graph". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 9 (26 de junio de 2023): 10900–10908. http://dx.doi.org/10.1609/aaai.v37i9.26292.
Texto completoZhang, Yizong, Shaobo Li, Qiuchen He, Ansi Zhang, Chuanjiang Li y Zihao Liao. "An Intelligent Fault Detection Framework for FW-UAV Based on Hybrid Deep Domain Adaptation Networks and the Hampel Filter". International Journal of Intelligent Systems 2023 (7 de junio de 2023): 1–19. http://dx.doi.org/10.1155/2023/6608967.
Texto completoLi, Xianling, Kai Zhang, Weijun Li, Yi Feng y Ruonan Liu. "A Two-Stage Transfer Regression Convolutional Neural Network for Bearing Remaining Useful Life Prediction". Machines 10, n.º 5 (12 de mayo de 2022): 369. http://dx.doi.org/10.3390/machines10050369.
Texto completoTong, Zhe, Wei Li, Bo Zhang y Meng Zhang. "Bearing Fault Diagnosis Based on Domain Adaptation Using Transferable Features under Different Working Conditions". Shock and Vibration 2018 (28 de junio de 2018): 1–12. http://dx.doi.org/10.1155/2018/6714520.
Texto completoAyalew, Melese, Shijie Zhou, Imran Memon, Md Belal Bin Heyat, Faijan Akhtar y Xiaojuan Zhang. "View-Invariant Spatiotemporal Attentive Motion Planning and Control Network for Autonomous Vehicles". Machines 10, n.º 12 (9 de diciembre de 2022): 1193. http://dx.doi.org/10.3390/machines10121193.
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