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 6301–6325 of 6439 papers

Title	Date	Tasks	Status
Domain adaptation for sequence labeling using hidden Markov models	Dec 14, 2013	Domain AdaptationPart-Of-Speech Tagging	—Unverified
Reshaping Visual Datasets for Domain Adaptation	Dec 1, 2013	Activity RecognitionDomain Adaptation	—Unverified
Non-Linear Domain Adaptation with Boosting	Dec 1, 2013	Domain AdaptationMulti-Task Learning	—Unverified
Domain Adaptation of Majority Votes via Perturbed Variation-based Label Transfer	Nov 19, 2013	Domain Adaptation	—Unverified
ML-Tuned Constraint Grammars	Nov 1, 2013	Domain Adaptation	—Unverified
Use of Combined Topic Models in Unsupervised Domain Adaptation for Word Sense Disambiguation	Nov 1, 2013	Domain AdaptationTopic Models	—Unverified
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition	Oct 6, 2013	ClusteringDomain Adaptation	CodeCode Available
Predicate Argument Structure Analysis using Partially Annotated Corpora	Oct 1, 2013	Domain AdaptationSemantic Role Labeling	—Unverified
An Online Algorithm for Learning over Constrained Latent Representations using Multiple Views	Oct 1, 2013	ChunkingDomain Adaptation	—Unverified
Towards Robust Cross-Domain Domain Adaptation for Part-of-Speech Tagging	Oct 1, 2013	Dimensionality ReductionDomain Adaptation	—Unverified
A Self-learning Template Approach for Recognizing Named Entities from Web Text	Oct 1, 2013	Domain AdaptationNamed Entity Recognition (NER)	—Unverified
A Common Case of Jekyll and Hyde: The Synergistic Effect of Using Divided Source Training Data for Feature Augmentation	Oct 1, 2013	Chinese Word SegmentationDomain Adaptation	—Unverified
JoBimText Visualizer: A Graph-based Approach to Contextualizing Distributional Similarity	Oct 1, 2013	Domain AdaptationGraph Clustering	—Unverified
Multi-Domain Adaptation for SMT Using Multi-Task Learning	Oct 1, 2013	Domain AdaptationMachine Translation	—Unverified
Learning Latent Word Representations for Domain Adaptation using Supervised Word Clustering	Oct 1, 2013	ClusteringDomain Adaptation	—Unverified
Semi-Supervised Representation Learning for Cross-Lingual Text Classification	Oct 1, 2013	ClassificationDocument Classification	—Unverified
Towards a Hybrid Rule-based and Statistical Arabic-French Machine Translation System	Sep 1, 2013	Domain AdaptationInformation Retrieval	—Unverified
Edit Distance: A New Data Selection Criterion for Domain Adaptation in SMT	Sep 1, 2013	Domain AdaptationInformation Retrieval	—Unverified
Revisiting the Old Kitchen Sink: Do we Need Sentiment Domain Adaptation?	Sep 1, 2013	Domain Adaptation	—Unverified
TwitIE: An Open-Source Information Extraction Pipeline for Microblog Text	Sep 1, 2013	Domain AdaptationNamed Entity Recognition (NER)	CodeCode Available
Towards Domain Adaptation for Parsing Web Data	Sep 1, 2013	Dependency ParsingDomain Adaptation	—Unverified
Domain Adaptation for Parsing	Sep 1, 2013	Dependency ParsingDomain Adaptation	—Unverified
Applications of Semantic Publishing	Sep 1, 2013	Domain Adaptation	—Unverified
Towards Adapting ImageNet to Reality: Scalable Domain Adaptation with Implicit Low-rank Transformations	Aug 20, 2013	Domain AdaptationScene Understanding	—Unverified
Dramatically Reducing Training Data Size Through Vocabulary Saturation	Aug 1, 2013	Domain AdaptationMachine Translation	—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	CMKD	Accuracy	89	—	Unverified
5	PMTrans	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	DDA	Accuracy	88.9	—	Unverified
9	MEDM	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