Visual Domain Adaptation with Manifold Embedded Distribution Alignment
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Philip S. Yu | Yiqiang Chen | Jindong Wang | Han Yu | Wenjie Feng | Meiyu Huang | Yiqiang Chen | Jindong Wang | Han Yu | Wenjie Feng | Meiyu Huang
[1] E. Denman,et al. The matrix sign function and computations in systems , 1976 .
[2] James Parker,et al. on Knowledge and Data Engineering, , 1990 .
[3] Mikhail Belkin,et al. Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples , 2006, J. Mach. Learn. Res..
[4] Koby Crammer,et al. Analysis of Representations for Domain Adaptation , 2006, NIPS.
[5] NiyogiPartha,et al. Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples , 2006 .
[6] Qiang Yang,et al. Boosting for transfer learning , 2007, ICML '07.
[7] Daniel D. Lee,et al. Grassmann discriminant analysis: a unifying view on subspace-based learning , 2008, ICML '08.
[8] Jun Huan,et al. Large margin transductive transfer learning , 2009, CIKM.
[9] Trevor Darrell,et al. Adapting Visual Category Models to New Domains , 2010, ECCV.
[10] Qiang Yang,et al. A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.
[11] Ivor W. Tsang,et al. Domain Adaptation via Transfer Component Analysis , 2009, IEEE Transactions on Neural Networks.
[12] Rama Chellappa,et al. Domain adaptation for object recognition: An unsupervised approach , 2011, 2011 International Conference on Computer Vision.
[13] Bernhard Schölkopf,et al. A Kernel Two-Sample Test , 2012, J. Mach. Learn. Res..
[14] Yuan Shi,et al. Geodesic flow kernel for unsupervised domain adaptation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[15] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[16] Ye Xu,et al. Unbiased Metric Learning: On the Utilization of Multiple Datasets and Web Images for Softening Bias , 2013, 2013 IEEE International Conference on Computer Vision.
[17] Tinne Tuytelaars,et al. Unsupervised Visual Domain Adaptation Using Subspace Alignment , 2013, 2013 IEEE International Conference on Computer Vision.
[18] Philip S. Yu,et al. Transfer Feature Learning with Joint Distribution Adaptation , 2013, 2013 IEEE International Conference on Computer Vision.
[19] Brian C. Lovell,et al. Unsupervised Domain Adaptation by Domain Invariant Projection , 2013, 2013 IEEE International Conference on Computer Vision.
[20] Philip S. Yu,et al. Adaptation Regularization: A General Framework for Transfer Learning , 2014, IEEE Transactions on Knowledge and Data Engineering.
[21] Trevor Darrell,et al. Deep Domain Confusion: Maximizing for Domain Invariance , 2014, CVPR 2014.
[22] Philip S. Yu,et al. Transfer Joint Matching for Unsupervised Domain Adaptation , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[23] Brian C. Lovell,et al. Domain Adaptation on the Statistical Manifold , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[24] Trevor Darrell,et al. DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition , 2013, ICML.
[25] Rémi Emonet,et al. Landmarks-based kernelized subspace alignment for unsupervised domain adaptation , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[26] Kate Saenko,et al. Subspace Distribution Alignment for Unsupervised Domain Adaptation , 2015, BMVC.
[27] Philip S. Yu,et al. Domain Invariant Transfer Kernel Learning , 2015, IEEE Transactions on Knowledge and Data Engineering.
[28] Kate Saenko,et al. Deep CORAL: Correlation Alignment for Deep Domain Adaptation , 2016, ECCV Workshops.
[29] Xuelong Li,et al. Discriminative Transfer Subspace Learning via Low-Rank and Sparse Representation , 2016, IEEE Transactions on Image Processing.
[30] Yu-Chiang Frank Wang,et al. Unsupervised Domain Adaptation With Label and Structural Consistency , 2016, IEEE Transactions on Image Processing.
[31] Jafar Tahmoresnezhad,et al. Visual domain adaptation via transfer feature learning , 2017, Knowledge and Information Systems.
[32] Kate Saenko,et al. Return of Frustratingly Easy Domain Adaptation , 2015, AAAI.
[33] Mehrtash Tafazzoli Harandi,et al. Distribution-Matching Embedding for Visual Domain Adaptation , 2016, J. Mach. Learn. Res..
[34] Qingming Huang,et al. Deep Unsupervised Convolutional Domain Adaptation , 2017, ACM Multimedia.
[35] Yiqiang Chen,et al. Balanced Distribution Adaptation for Transfer Learning , 2017, 2017 IEEE International Conference on Data Mining (ICDM).
[36] Mengjie Zhang,et al. Scatter Component Analysis: A Unified Framework for Domain Adaptation and Domain Generalization , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[37] Hui Xiong,et al. A Unified Framework for Metric Transfer Learning , 2017, IEEE Transactions on Knowledge and Data Engineering.
[38] Jing Zhang,et al. Joint Geometrical and Statistical Alignment for Visual Domain Adaptation , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[39] Henning Müller,et al. Datasets column: diversity and credibility for social images and image retrieval , 2018, ACMMR.
[40] Jianmin Wang,et al. Unsupervised Domain Adaptation With Distribution Matching Machines , 2018, AAAI.
[41] Wei Liu,et al. Zero-Shot Visual Recognition Using Semantics-Preserving Adversarial Embedding Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.