A theory of learning from different domains

Shai Ben-David; John Blitzer; Koby Crammer; Alex Kulesza; Fernando Pereira; Jennifer Wortman Vaughan

doi:https://doi.org/10.1007/s10994-009-5152-4

A theory of learning from different domains

2009 · Machine Learning · 3,607 citations · 7 from inside this corpus

Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza low, Fernando Pereira, Jennifer Wortman Vaughan

The source holds an abstract for this work, but its best open-access copy is under cc-by-nc, which does not permit us to republish the text. Read it at the source below.

20 of 20 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.

this paper works it cites works citing it node size = global citations · hover for the full title

Citation edge evidence

Each row is directed from the citing work to the cited work. Source status remains readable without the interactive graph.

Domain-Adversarial Training of Neural Networks→A theory of learning from different domainsLegacy edge — source detail unavailable
Advances and Open Problems in Federated Learning→A theory of learning from different domainsLegacy edge — source detail unavailable
Learning Transferable Features with Deep Adaptation Networks→A theory of learning from different domainsLegacy edge — source detail unavailable
Maximum Classifier Discrepancy for Unsupervised Domain Adaptation→A theory of learning from different domainsLegacy edge — source detail unavailable
On the Opportunities and Risks of Foundation Models→A theory of learning from different domainsLegacy edge — source detail unavailable
Deep Hashing Network for Unsupervised Domain Adaptation→A theory of learning from different domainsLegacy edge — source detail unavailable
Moment Matching for Multi-Source Domain Adaptation→A theory of learning from different domainsLegacy edge — source detail unavailable
A theory of learning from different domains→Statistical Learning TheoryLegacy edge — source detail unavailable
A theory of learning from different domains→Thumbs up?Legacy edge — source detail unavailable
A theory of learning from different domains→Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of …Legacy edge — source detail unavailable
A theory of learning from different domains→Thumbs up? Sentiment Classification using Machine Learning TechniquesLegacy edge — source detail unavailable
A theory of learning from different domains→Rademacher and Gaussian Complexities: Risk Bounds and Structural ResultsLegacy edge — source detail unavailable
A theory of learning from different domains→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
A theory of learning from different domains→Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classifi…Legacy edge — source detail unavailable
A theory of learning from different domains→Head-Driven Statistical Models for Natural Language ParsingLegacy edge — source detail unavailable
A theory of learning from different domains→Boosting for transfer learningLegacy edge — source detail unavailable
A theory of learning from different domains→Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of …Legacy edge — source detail unavailable
A theory of learning from different domains→Correcting Sample Selection Bias by Unlabeled DataLegacy edge — source detail unavailable
A theory of learning from different domains→Frustratingly Easy Domain AdaptationLegacy edge — source detail unavailable
A theory of learning from different domains→A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled DataLegacy edge — source detail unavailable
Domain-Adversarial Training of Neural Networks→Correcting Sample Selection Bias by Unlabeled DataLegacy edge — source detail unavailable
Domain-Adversarial Training of Neural Networks→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
Frustratingly Easy Domain Adaptation→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
Boosting for transfer learning→Correcting Sample Selection Bias by Unlabeled DataLegacy edge — source detail unavailable
A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data→Statistical Learning TheoryLegacy edge — source detail unavailable
Analysis of Representations for Domain Adaptation→Statistical Learning TheoryLegacy edge — source detail unavailable
Learning Transferable Features with Deep Adaptation Networks→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classifi…→A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled DataLegacy edge — source detail unavailable
Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classifi…→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classifi…→Thumbs up?Legacy edge — source detail unavailable
Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classifi…→Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of …Legacy edge — source detail unavailable
Thumbs up?→Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of …Legacy edge — source detail unavailable
Thumbs up?→Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of …Legacy edge — source detail unavailable
Deep Hashing Network for Unsupervised Domain Adaptation→Domain-Adversarial Training of Neural NetworksLegacy edge — source detail unavailable
Deep Hashing Network for Unsupervised Domain Adaptation→Learning Transferable Features with Deep Adaptation NetworksLegacy edge — source detail unavailable
Thumbs up? Sentiment Classification using Machine Learning Techniques→Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of …Legacy edge — source detail unavailable
Maximum Classifier Discrepancy for Unsupervised Domain Adaptation→Domain-Adversarial Training of Neural NetworksLegacy 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
Moment Matching for Multi-Source Domain Adaptation→Analysis of Representations for Domain AdaptationLegacy 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 Hashing Network for Unsupervised Domain AdaptationLegacy edge — source detail unavailable
Moment Matching for Multi-Source Domain Adaptation→Maximum Classifier Discrepancy for Unsupervised Domain AdaptationLegacy edge — source detail unavailable
On the Opportunities and Risks of Foundation Models→Frustratingly Easy Domain AdaptationLegacy edge — source detail unavailable
On the Opportunities and Risks of Foundation Models→Moment Matching for Multi-Source Domain AdaptationLegacy edge — source detail unavailable

What this paper cites, inside the corpus

Paper	Year	Cited
Statistical Learning Theory	1999	26,957
Thumbs up?	2002	7,057
Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of …	2002	3,661
Thumbs up? Sentiment Classification using Machine Learning Techniques	2002	2,215
Rademacher and Gaussian Complexities: Risk Bounds and Structural Results	2001	2,126
Analysis of Representations for Domain Adaptation	2007	2,044
Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classifi…	2007	2,031
Head-Driven Statistical Models for Natural Language Parsing	2003	1,861
Boosting for transfer learning	2007	1,748
Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of …	2002	1,586
Correcting Sample Selection Bias by Unlabeled Data	2007	1,566
Frustratingly Easy Domain Adaptation	2009	1,396
A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data	2005	1,370

What cites it, inside the corpus

Paper	Year	Cited
Domain-Adversarial Training of Neural Networks	2017	7,702
Advances and Open Problems in Federated Learning	2020	5,383
Learning Transferable Features with Deep Adaptation Networks	2015	2,839
Maximum Classifier Discrepancy for Unsupervised Domain Adaptation	2018	2,280
On the Opportunities and Risks of Foundation Models	2021	2,265
Deep Hashing Network for Unsupervised Domain Adaptation	2017	2,081
Moment Matching for Multi-Source Domain Adaptation	2019	1,643

Links

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Topics

Domain Adaptation and Few-Shot Learning	Computer Science
Machine Learning and Algorithms	Computer Science
Machine Learning and Data Classification	Computer Science

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complete

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supports6 author record(s) attached.
supports44 reference(s) recorded.
neutralThe DOI carries no year to check against.
supportsA title is present.

Provenance

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