Mingsheng Long, Jianmin Wang*, Jia-Guang Sun, Philip S. Yu:Domain Invariant Transfer Kernel Learning. (6)(2015) 来自 Semantic Scholar 喜欢 0 阅读量: 70 作者: 王建民 年份: 2015 收藏 引用 批量引用 报错 分享 全部来源 求助全文 Semantic Scholar or.nsfc.gov.cn 相似文献...
领域不变性迁移核学习(Transfer Kernel Learning, TKL) Domain invariant transfer kernel learning 发表在IEEE Trans. Knowledge and Data Engineering期刊上 深度适配网络(Deep Adaptation Network, DAN) 发表在ICML-15上:learning transferable features with deep adaptation networks 我的解读 深度联合适配网络(Joint Adap...
Domain-invariant representation learning领域不变表示学习, which performs kernel, adversarial training, explicitly feature alignment(核技巧、对抗学习、显式特征对齐) between domains, or invariant risk minimization to learn domain invariant representations(学习领域不变表示); b). Feature disentanglement(特征解耦...
Bruzzone, "Kernel-Based Domain-Invariant Feature Selection in Hyperspectral Images for Transfer Learning," IEEE Trans. Geosci. Remote Sens., vol. 54, no. 5, pp.. 2615-2626, 2016.C. Persello and L. Bruzzone, "Kernel-based domain-invariant feature se- lection in hyperspectral images for ...
Domain Invariant Transfer Kernel Learning Domain transfer learning generalizes a learning model across training data and testing data with different distributions. A general principle to tackle thi... M Long,J Wang,J Sun,... - 《IEEE Transactions on Knowledge & Data Engineering》 被引量: 72发表...
Gated Domain-Invariant Feature Disentanglement for Domain Generalizable Object Detection Channel masking for domain generalization object detection 通过一个gate控制channel masking进行object detection DG A Broad Study of Pre-training for Domain Generalization and Adaptation ...
P(B|I)Domain Invariant bbox predictor P(B|D,I)Domains dependent box predictor 网络结构与损失函数 在Faster-RCNN基础上,CNN-Backbone的Feature Map直接做Image level的Alignment,通过GRL+Conv实现Image Level对齐;目标检测回归之后的Feature Map,通过GRL+FC实现Instance Level对齐。
This means the model can better utilize the knowledge from the source domain in the target domain without falling into the trap of negative transfer. By combining these methods, we ensure that the model is not only capable of learning domain-invariant features but also of discovering class-...
Theory and algorithm of domain-invariant learning for transfer learning 对invariant representation的理论和算法 WACV-22 Semi-supervised Domain Adaptation via Sample-to-Sample Self-Distillation Sample-level self-distillation for semi-supervised DA 样本层次的自蒸馏用于半监督DA ROBIN : A Benchmark for Robust...
ICLR-22 Asymmetry Learning for Counterfactually-invariant Classification in OOD Tasks Asymmetry learning for OOD tasks 非对称学习用于OOD任务1.Introduction and Tutorials (简介与教程)Want to quickly learn transfer learning?想尽快入门迁移学习?看下面的教程。Books...