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 6376–6400 of 6439 papers

Title	Date	Tasks	Status
Simple and Effective Parameter Tuning for Domain Adaptation of Statistical Machine Translation	Dec 1, 2012	Domain AdaptationMachine Translation	—Unverified
A Simplification-Translation-Restoration Framework for Cross-Domain SMT Applications	Dec 1, 2012	Domain AdaptationMachine Translation	—Unverified
Translation Quality-Based Supplementary Data Selection by Incremental Update of Translation Models	Dec 1, 2012	Domain AdaptationMachine Translation	—Unverified
Topic Modeling-based Domain Adaptation for System Combination	Dec 1, 2012	Document ClassificationDomain Adaptation	—Unverified
Traditional Chinese Parsing Evaluation at SIGHAN Bake-offs 2012	Dec 1, 2012	Dependency ParsingDomain Adaptation	—Unverified
Semi-Supervised Domain Adaptation with Non-Parametric Copulas	Dec 1, 2012	Domain Adaptationregression	—Unverified
Shifting Weights: Adapting Object Detectors from Image to Video	Dec 1, 2012	Domain AdaptationEvent Detection	—Unverified
Automatic Domain Adaptation for Word Sense Disambiguation Based on Comparison of Multiple Classifiers	Nov 1, 2012	Domain AdaptationWord Sense Disambiguation	—Unverified
Accurate Unsupervised Joint Named-Entity Extraction from Unaligned Parallel Text	Jul 1, 2012	Cross-Domain Named Entity RecognitionDomain Adaptation	—Unverified
Dialogue Act Recognition using Reweighted Speaker Adaptation	Jul 1, 2012	Dialogue UnderstandingDomain Adaptation	—Unverified
Domain Adaptation for Coreference Resolution: An Adaptive Ensemble Approach	Jul 1, 2012	coreference-resolutionCoreference Resolution	—Unverified
Biased Representation Learning for Domain Adaptation	Jul 1, 2012	Domain AdaptationRepresentation Learning	—Unverified
Improved Parsing and POS Tagging Using Inter-Sentence Consistency Constraints	Jul 1, 2012	Dependency ParsingDomain Adaptation	—Unverified
Linking Named Entities to Any Database	Jul 1, 2012	Domain AdaptationEntity Linking	—Unverified
Do Neighbours Help? An Exploration of Graph-based Algorithms for Cross-domain Sentiment Classification	Jul 1, 2012	Domain AdaptationGeneral Classification	—Unverified
Multi-Domain Learning: When Do Domains Matter?	Jul 1, 2012	Domain AdaptationSentiment Analysis	—Unverified
Active Learning with Transfer Learning	Jul 1, 2012	Active LearningDomain Adaptation	—Unverified
Grammar Error Correction Using Pseudo-Error Sentences and Domain Adaptation	Jul 1, 2012	Domain AdaptationMachine Translation	—Unverified
Domain Adaptation of a Dependency Parser with a Class-Class Selectional Preference Model	Jul 1, 2012	Dependency ParsingDomain Adaptation	—Unverified
Information-theoretic Multi-view Domain Adaptation	Jul 1, 2012	Document ClassificationDomain Adaptation	—Unverified
Cross-Domain Co-Extraction of Sentiment and Topic Lexicons	Jul 1, 2012	Domain AdaptationInformation Retrieval	—Unverified
Corpus-based Interpretation of Instructions in Virtual Environments	Jul 1, 2012	Domain AdaptationText Generation	—Unverified
Translation Model Adaptation for Statistical Machine Translation with Monolingual Topic Information	Jul 1, 2012	Domain AdaptationInformation Retrieval	—Unverified
Bootstrapping via Graph Propagation	Jul 1, 2012	Domain Adaptation	CodeCode Available
Mixing Multiple Translation Models in Statistical Machine Translation	Jul 1, 2012	Domain AdaptationLanguage Modelling	—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