Discriminative and domain invariant subspace alignment for visual tasksUnsupervised domain adaptationGlobal adaptationLocal adaptationDistinct transformationMaximum mean discrepancyTransfer learning and domain adaptation are promising solutions to solve the problem that the training set (source domain) and the test...
Domain invariant and class discriminative heterogeneous domain adaptation 2018 IEEE 3rd international conference on communication and information systems (ICCIS), IEEE (2018), pp. 227-231 Google Scholar Wang et al., 2019 Wang X., Jin Y., Long M., Wang J., Jordan M.I. Transferable normalizatio...
featurelearningmethodarepro-posed,bothofwhichguaranteethedomaininvariantfeatureswithbetterintra-classcompactnessandinter-classseparabil-ity.Extensiveexperimentsshowthatlearningthediscrimi-nativefeaturesinthesharedfeaturespacecansignificantlyboosttheperformanceofdeepdomainadaptationmethods.IntroductionDomainadaptation,which...
Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation Domain adaptation manages to build an effective target classifier or regression model for unlabeled target data by utilizing the well-labeled source data b... S Li,S Song,H Gao,... - 《IEEE Transactions on Ima...
Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation [TIP 2018] Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation [ECCV2018] Aligning Infinite-Dimensional Covariance Matrices in Reproducing Kernel Hilbert Spaces for Domain Adaptation [CVPR2018] Unsupervised ...
DICD Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation TIP2018 HDANA Heterogeneous Domain Adaptation Network Based on Autoencoder JPDC2018 DKTL Domain Class Consistency Based Transfer Learning For Image Classification Across Domains InforSci2017 Ding's Deep Domai...
内容提示: Exploiting Both Domain-specif i c and Invariant Knowledge via a Win-winTransformer for Unsupervised Domain AdaptationWenxuan Ma 1∗ JinMing Zhang 1∗ Shuang Li 1† Chi Harold Liu 1 Yulin Wang 2 Wei Li 31 Beijing Institute of Technology 2 Tsinghua University 3 Inceptio Tech.{...
以数据为中心的方法(data centric methods ) 寻求一个统一的转换,将数据从source domain和target domain投影到域不变空间(domain invariant space)当中,以求减少source domain和target domain上数据的分布差异(distributional divergence),并且同时保留原始空间当中的数据属性 ...
Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation[TIP 2018] Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation[ECCV2018] Aligning Infinite-Dimensional Covariance Matrices in Reproducing Kernel Hilbert Spaces for Domain Adaptation[CVPR2018] ...
Deep Discriminative Learning for Unsupervised Domain Adaptation [arXiv 17 Nov 2018] Unsupervised Domain Adaptation for Distance Metric Learning [ICLR2019] Co-regularized Alignment for Unsupervised Domain Adaptation [NIPS2018] Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptatio...