Topic: heterogeneous-domain-adaptation Goto Github
Some thing interesting about heterogeneous-domain-adaptation
Some thing interesting about heterogeneous-domain-adaptation
heterogeneous-domain-adaptation,[ACMMM 2020] Code release for "Simultaneous Semantic Alignment Network for Heterogenous Domain Adaptation" https://arxiv.org/abs/2008.01677
Organization: bit-da
Home Page: https://arxiv.org/abs/2008.01677
heterogeneous-domain-adaptation,We present a framework called TLF that builds a classifier for the target domain having only few labeled training records by transferring knowledge from the source domain having many labeled records. While existing methods often focus on one issue and leave the other one for the further work, TLF is capable of handling both issues simultaneously. In TLF, we alleviate feature discrepancy by identifying shared label distributions that act as the pivots to bridge the domains. We handle distribution divergence by simultaneously optimizing the structural risk functional, joint distributions between domains, and the manifold consistency underlying marginal distributions. Moreover, for the manifold consistency we exploit its intrinsic properties by identifying $k$ nearest neighbors of a record, where the value of k is determined automatically in TLF. Furthermore, since negative transfer is not desired, we consider only the source records that are belonging to the source pivots during the knowledge transfer. We evaluate TLF on seven publicly available natural datasets and compare the performance of TLF against the performance of eleven state-of-the-art techniques. We also evaluate the effectiveness of TLF in some challenging situations. Our experimental results, including statistical sign test and Nemenyi test analyses, indicate a clear superiority of the proposed framework over the state-of-the-art techniques.
User: grahman20
Home Page: https://csusap.csu.edu.au/~grahman/
heterogeneous-domain-adaptation,Cross Domain Structure Preserving Projection for Heterogeneous Domain Adaptation
User: hellowangqian
heterogeneous-domain-adaptation,📜 [MIDL 2022] "Sensor to Image Heterogeneous Domain Adaptation Network", Ishikaa Lunawat, Vignesh S, S P Sharan
Organization: spidernitt
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