Moment Matching for Multi-Source Domain Adaptation
Xingchao Peng low, Qinxun Bai, Xide Xia low, Zijun Huang, Kate Saenko, Bo Wang
The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.
this paper
works it cites
works citing it
node size = global citations · hover for the full title
Citation edge evidence
- On the Opportunities and Risks of Foundation Models→Moment Matching for Multi-Source Domain AdaptationLegacy edge — source detail unavailable
- Moment Matching for Multi-Source Domain Adaptation→A Survey on Transfer LearningLegacy edge — source detail unavailable
- Moment Matching for Multi-Source Domain Adaptation→Adversarial Discriminative Domain AdaptationLegacy edge — source detail unavailable
- Moment Matching for Multi-Source Domain Adaptation→A theory of learning from different domainsLegacy edge — source detail unavailable
- Moment Matching for Multi-Source Domain Adaptation→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- Moment Matching for Multi-Source Domain Adaptation→Learning Transferable Features with Deep Adaptation NetworksLegacy edge — source detail unavailable
- Moment Matching for Multi-Source Domain Adaptation→Deep Domain Confusion: Maximizing for Domain InvarianceLegacy edge — source detail unavailable
- Moment Matching for Multi-Source Domain Adaptation→Maximum Classifier Discrepancy for Unsupervised Domain AdaptationLegacy edge — source detail unavailable
- Moment Matching for Multi-Source Domain Adaptation→Geodesic flow kernel for unsupervised domain adaptationLegacy edge — source detail unavailable
- Moment Matching for Multi-Source Domain Adaptation→Deep Hashing Network for Unsupervised Domain AdaptationLegacy edge — source detail unavailable
- Moment Matching for Multi-Source Domain Adaptation→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
- Moment Matching for Multi-Source Domain Adaptation→A Kernel Method for the Two-Sample-ProblemLegacy edge — source detail unavailable
- Moment Matching for Multi-Source Domain Adaptation→Return of Frustratingly Easy Domain AdaptationLegacy edge — source detail unavailable
- Deep Domain Confusion: Maximizing for Domain Invariance→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- Deep Domain Confusion: Maximizing for Domain Invariance→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
- A theory of learning from different domains→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
- A Kernel Method for the Two-Sample-Problem→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
- Geodesic flow kernel for unsupervised domain adaptation→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- Geodesic flow kernel for unsupervised domain adaptation→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
- Geodesic flow kernel for unsupervised domain adaptation→A Survey on Transfer LearningLegacy edge — source detail unavailable
- Learning Transferable Features with Deep Adaptation Networks→Deep Domain Confusion: Maximizing for Domain InvarianceLegacy edge — source detail unavailable
- Learning Transferable Features with Deep Adaptation Networks→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- Learning Transferable Features with Deep Adaptation Networks→A theory of learning from different domainsLegacy edge — source detail unavailable
- Learning Transferable Features with Deep Adaptation Networks→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
- Learning Transferable Features with Deep Adaptation Networks→Geodesic flow kernel for unsupervised domain adaptationLegacy edge — source detail unavailable
- Learning Transferable Features with Deep Adaptation Networks→A Survey on Transfer LearningLegacy edge — source detail unavailable
- A Survey on Transfer Learning→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
- Adversarial Discriminative Domain Adaptation→Deep Domain Confusion: Maximizing for Domain InvarianceLegacy edge — source detail unavailable
- Adversarial Discriminative Domain Adaptation→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- Adversarial Discriminative Domain Adaptation→Learning Transferable Features with Deep Adaptation NetworksLegacy edge — source detail unavailable
- Adversarial Discriminative Domain Adaptation→Return of Frustratingly Easy Domain AdaptationLegacy edge — source detail unavailable
- Deep Hashing Network for Unsupervised Domain Adaptation→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- Deep Hashing Network for Unsupervised Domain Adaptation→A theory of learning from different domainsLegacy edge — source detail unavailable
- Deep Hashing Network for Unsupervised Domain Adaptation→Geodesic flow kernel for unsupervised domain adaptationLegacy edge — source detail unavailable
- Deep Hashing Network for Unsupervised Domain Adaptation→Learning Transferable Features with Deep Adaptation NetworksLegacy edge — source detail unavailable
- Deep Hashing Network for Unsupervised Domain Adaptation→A Survey on Transfer LearningLegacy edge — source detail unavailable
- Deep Hashing Network for Unsupervised Domain Adaptation→Return of Frustratingly Easy Domain AdaptationLegacy edge — source detail unavailable
- Maximum Classifier Discrepancy for Unsupervised Domain Adaptation→Deep Domain Confusion: Maximizing for Domain InvarianceLegacy edge — source detail unavailable
- Maximum Classifier Discrepancy for Unsupervised Domain Adaptation→A theory of learning from different domainsLegacy edge — source detail unavailable
- Maximum Classifier Discrepancy for Unsupervised Domain Adaptation→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
- Maximum Classifier Discrepancy for Unsupervised Domain Adaptation→Learning Transferable Features with Deep Adaptation NetworksLegacy edge — source detail unavailable
- Maximum Classifier Discrepancy for Unsupervised Domain Adaptation→Adversarial Discriminative Domain AdaptationLegacy edge — source detail unavailable
- Maximum Classifier Discrepancy for Unsupervised Domain Adaptation→Return of Frustratingly Easy Domain AdaptationLegacy edge — source detail unavailable
- Return of Frustratingly Easy Domain Adaptation→Deep Domain Confusion: Maximizing for Domain InvarianceLegacy edge — source detail unavailable
- Return of Frustratingly Easy Domain Adaptation→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- Return of Frustratingly Easy Domain Adaptation→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
- Return of Frustratingly Easy Domain Adaptation→Geodesic flow kernel for unsupervised domain adaptationLegacy edge — source detail unavailable
- Return of Frustratingly Easy Domain Adaptation→Learning Transferable Features with Deep Adaptation NetworksLegacy edge — source detail unavailable
- On the Opportunities and Risks of Foundation Models→A theory of learning from different domainsLegacy edge — source detail unavailable
What this paper cites, inside the corpus
What cites it, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| On the Opportunities and Risks of Foundation Models | 2021 | 2,265 |
Links
Topics
| Domain Adaptation and Few-Shot Learning | Computer Science |
| Multimodal Machine Learning Applications | Computer Science |
| Cancer-related molecular mechanisms research | Biochemistry, Genetics and Molecular Biology |
Is this record sound?
complete
Nothing in this record contradicts itself and no field we check is missing.
- supports6 author record(s) attached.
- supports82 reference(s) recorded.
- supportsThe DOI's year agrees with the publication year.
- supportsA title is present.
Provenance
sha256 7bc26169e93749d1…