Domain Adaptation Information Bottleneck

Ibdapi is an information theoretic principle for extracting relevant infor.

Domain adaptation information bottleneck. No domain bias and much less knows about carrying auxiliary information over to a new domain. Since the two domains essentially overlap in semantic level such pu rified features can facilitate the following alignment and stabilize the adversarial training course. Since informa tion bottleneck method has been successfully applied to supervised learning 1 generative modeling 13 25 and reinforcement learn ing 25 in the context of domain adaptation we propose to exploit.

Improving unsupervised domain adaptation with variational information bottleneck inproceedings song2020improvingud title improving unsupervised domain adaptation with variational information bottleneck author yuxuan song and lantao yu and zhangjie cao and zhiming zhou and jian shen and shuo shao and w. In visual domain adaptation scenarios the domain invariant a k a. The information bottleneck filters out the nuisance factors and maintains pure semantic information.

Domain adaptation for semantic segmentation with maximum squares loss. Learning to learn with variational information bottleneck for domain generalization yingjun du1 0000 0001 7537 6457 jun xu2 huan xiong4 qiang qiu5 xiantong zhen1 3 cees g. Self ensembling with gan based data augmentation for domain adaptation in semantic segmentation.

Information bottleneck before the adversarial feature adap tation. Information bottleneck domain adaptation with privileged information 3 uda uda lupi svm sgf lmk sa lmibda da m2s lmibdapi 17 94 18 22 18 36 19 19 26 15 30 74 33 66 table2 rgb d caltech 256dataset classification accuracies for the multi class classification with linear kernel. Main and auxiliary views are kdes features of the rgb and depth of the.

Propose to regularize domain adaptation models with information bottleneck principle 35 which seeks to find the optimal tradeoff between representation accuracy and compression. Significance aware information bottleneck for domain adaptive semantic segmentation. This paper proposes an adapted information bottleneck method for the construction of domain oriented sentiment lexicon.

Ibdapi is an information theoretic principle for extracting relevant information from the target view but gives an implicit hence computationally hard way for learning a visual classifier based on such information. Snoek1 and ling shao3 4 1 aim lab university of amsterdam the netherlands 2 college of computer science nankai university china 3 inception institute of arti cial intelligence abu dhabi uae. Transferable representations 36 are considered to be the information bottleneck to enhance the generalizability of a model transferred from labeled source domain to unlabeled or weakly labeled target domain.