Domain Adaptation

Domain Adaptation is the task of adapting models across domains. This is motivated by the challenge where the test and training datasets fall from different data distributions due to some factor. Domain adaptation aims to build machine learning models that can be generalized into a target domain and dealing with the discrepancy across domain distributions.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 4976–5000 of 6439 papers

Title	Date	Tasks	Status
Relation Adversarial Network for Low Resource Knowledge Graph Completion	Nov 8, 2019	Domain AdaptationKnowledge Graph Completion	—Unverified
The TechQA Dataset	Nov 8, 2019	Domain AdaptationQuestion Answering	CodeCode Available
Graph Domain Adaptation with Localized Graph Signal Representations	Nov 7, 2019	Domain AdaptationGRAPH DOMAIN ADAPTATION	—Unverified
Towards Domain Adaptation from Limited Data for Question Answering Using Deep Neural Networks	Nov 6, 2019	Domain AdaptationQuestion Answering	—Unverified
Unsupervised Domain Adaptation of Contextual Embeddings for Low-Resource Duplicate Question Detection	Nov 6, 2019	Domain AdaptationKnowledge Graphs	—Unverified
Federated Adversarial Domain Adaptation	Nov 5, 2019	DisentanglementDomain Adaptation	—Unverified
Fairness Violations and Mitigation under Covariate Shift	Nov 2, 2019	Domain AdaptationFairness	—Unverified
Domain Adaptation with BERT-based Domain Classification and Data Selection	Nov 1, 2019	ClassificationDomain Adaptation	—Unverified
Fast Domain Adaptation of Semantic Parsers via Paraphrase Attention	Nov 1, 2019	Domain Adaptation	—Unverified
NICT's participation to WAT 2019: Multilingualism and Multi-step Fine-Tuning for Low Resource NMT	Nov 1, 2019	Domain AdaptationLow Resource NMT	—Unverified
Generic and Specialized Word Embeddings for Multi-Domain Machine Translation	Nov 1, 2019	Domain AdaptationMachine Translation	—Unverified
Forget Me Not: Reducing Catastrophic Forgetting for Domain Adaptation in Reading Comprehension	Nov 1, 2019	Domain AdaptationReading Comprehension	CodeCode Available
Air-Writing Translater: A Novel Unsupervised Domain Adaptation Method for Inertia-Trajectory Translation of In-air Handwriting	Nov 1, 2019	Domain AdaptationTranslation	—Unverified
Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back-Translation	Nov 1, 2019	Data AugmentationDiversity	CodeCode Available
Extreme Learning Machine-Based Heterogeneous Domain Adaptation for Classification of Hyperspectral Images	Nov 1, 2019	ClassificationClassification Of Hyperspectral Images	—Unverified
Biomedical Relation Classification by single and multiple source domain adaptation	Nov 1, 2019	ClassificationDomain Adaptation	—Unverified
Domain Adaptation for Person-Job Fit with Transferable Deep Global Match Network	Nov 1, 2019	Domain AdaptationSentence	—Unverified
Domain Adaptation of Document-Level NMT in IWSLT19	Nov 1, 2019	Domain AdaptationNMT	—Unverified
Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning	Oct 31, 2019	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available
Machine Translation of Restaurant Reviews: New Corpus for Domain Adaptation and Robustness	Oct 31, 2019	Domain AdaptationMachine Translation	—Unverified
Deep Metric Learning-Based Feature Embedding for Hyperspectral Image Classification	Oct 30, 2019	Domain AdaptationFew-Shot Image Classification	CodeCode Available
Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation	Oct 29, 2019	Domain AdaptationSemantic Segmentation	CodeCode Available
Cross lingual transfer learning for zero-resource domain adaptation	Oct 29, 2019	Acoustic ModellingCross-Lingual Transfer	—Unverified
Deep causal representation learning for unsupervised domain adaptation	Oct 28, 2019	Domain AdaptationRepresentation Learning	—Unverified
Multi-sequence Cardiac MR Segmentation with Adversarial Domain Adaptation Network	Oct 28, 2019	Domain AdaptationManagement	—Unverified

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All datasets Office-31 SYNTHIA-to-Cityscapes GTA5 to Cityscapes Office-Home VisDA2017 ImageCLEF-DA Cityscapes to ACDC MNIST-to-USPS SVHN-to-MNIST USPS-to-MNIST SVNH-to-MNIST MoLane

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	FFTAT	Average Accuracy	96	—	Unverified
2	PMTrans	Average Accuracy	95.3	—	Unverified
3	CMKD	Average Accuracy	94.4	—	Unverified
4	SSRT-B (ours)	Average Accuracy	93.5	—	Unverified
5	CDTrans	Average Accuracy	92.6	—	Unverified
6	CoVi	Average Accuracy	91.8	—	Unverified
7	GSDE	Average Accuracy	91.7	—	Unverified
8	FixBi	Average Accuracy	91.4	—	Unverified
9	Contrastive Adaptation Network	Average Accuracy	90.6	—	Unverified
10	BIWAA	Average Accuracy	90.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HALO	mIoU	78.1	—	Unverified
2	ILM-ASSL	mIoU	76.6	—	Unverified
3	DCF	mIoU	69.3	—	Unverified
4	HRDA+PiPa	mIoU	68.2	—	Unverified
5	MIC	mIoU	67.3	—	Unverified
6	FREDOM - Transformer	mIoU	67	—	Unverified
7	HRDA	mIoU	65.8	—	Unverified
8	SePiCo	mIoU	64.3	—	Unverified
9	MIC + Guidance Training	mIoU	63.8	—	Unverified
10	DAFormer + ProCST	mIoU	61.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HALO	mIoU	77.8	—	Unverified
2	DCF	mIoU	77.7	—	Unverified
3	ILM-ASSL	mIoU	76.1	—	Unverified
4	MIC	mIoU	75.9	—	Unverified
5	HRDA+PiPa	mIoU	75.6	—	Unverified
6	HRDA	mIoU	73.8	—	Unverified
7	FREDOM - Transformer	mIoU	73.6	—	Unverified
8	HALO	mIoU	73.3	—	Unverified
9	SePiCo	mIoU	70.3	—	Unverified
10	DAFormer + ProCST	mIoU	69.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SWG	Accuracy	92.3	—	Unverified
2	RCL	Accuracy	90	—	Unverified
3	PGA (ViT-L/14)	Accuracy	89.4	—	Unverified
4	PMTrans	Accuracy	89	—	Unverified
5	CMKD	Accuracy	89	—	Unverified
6	MIC	Accuracy	86.2	—	Unverified
7	PGA (ViT-B/16)	Accuracy	85.1	—	Unverified
8	ELS	Accuracy	84.6	—	Unverified
9	SDAT (ViT-B/16)	Accuracy	84.3	—	Unverified
10	CDTrans (DeiT-B)	Accuracy	80.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FFTAT	Accuracy	93.8	—	Unverified
2	RCL	Accuracy	93.2	—	Unverified
3	MIC	Accuracy	92.8	—	Unverified
4	SWG	Accuracy	92.7	—	Unverified
5	CMKD	Accuracy	91.8	—	Unverified
6	DePT	Accuracy	90.7	—	Unverified
7	SDAT(ViT)	Accuracy	89.8	—	Unverified
8	SFDA2++	Accuracy	89.6	—	Unverified
9	PMtrans	Accuracy	88.8	—	Unverified
10	CoVi	Accuracy	88.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CMKD	Accuracy	94.3	—	Unverified
2	MCC+NWD	Accuracy	90.7	—	Unverified
3	GLOT-DR	Accuracy	90.4	—	Unverified
4	SPL	Accuracy	90.3	—	Unverified
5	DFA-SAFN	Accuracy	90.2	—	Unverified
6	DADA	Accuracy	89.3	—	Unverified
7	DFA-ENT	Accuracy	89.1	—	Unverified
8	MEDM	Accuracy	88.9	—	Unverified
9	DDA	Accuracy	88.9	—	Unverified
10	IAFN+ENT	Accuracy	88.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SoRA	mIoU	78.8	—	Unverified
2	Rein	mIoU	77.6	—	Unverified
3	CoDA	mIoU	72.6	—	Unverified
4	Refign (HRDA)	mIoU	72.1	—	Unverified
5	HALO	mIoU	71.9	—	Unverified
6	MIC	mIoU	70.4	—	Unverified
7	HRDA	mIoU	68	—	Unverified
8	Refign (DAFormer)	mIoU	65.5	—	Unverified
9	VBLC (DAFormer)	mIoU	64.2	—	Unverified
10	CMFormer	mIoU	60.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FACT	Accuracy	98.8	—	Unverified
2	FAMCD	Accuracy	98.72	—	Unverified
3	DFA-MCD	Accuracy	98.6	—	Unverified
4	Mean teacher	Accuracy	98.26	—	Unverified
5	DRANet	Accuracy	98.2	—	Unverified
6	SHOT	Accuracy	98	—	Unverified
7	DFA-ENT	Accuracy	97.9	—	Unverified
8	CyCleGAN (Light-weight Calibrator)	Accuracy	97.1	—	Unverified