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Multi-Task Learning

Multi-task learning aims to learn multiple different tasks simultaneously while maximizing performance on one or all of the tasks.

( Image credit: Cross-stitch Networks for Multi-task Learning )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 3401–3410 of 3687 papers

Title	Date	Tasks	Status	Hype
MTNA: A Neural Multi-task Model for Aspect Category Classification and Aspect Term Extraction On Restaurant Reviews	Nov 1, 2017	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
Extracting Important Tweets for News Writers using Recurrent Neural Network with Attention Mechanism and Multi-task Learning	Nov 1, 2017	Multi-Task Learning	—Unverified	0
Proofread Sentence Generation as Multi-Task Learning with Editing Operation Prediction	Nov 1, 2017	ArticlesGrammatical Error Correction	—Unverified	0
Understanding and Improving Morphological Learning in the Neural Machine Translation Decoder	Nov 1, 2017	DecoderMachine Translation	—Unverified	0
A Multi-task Learning Approach to Adapting Bilingual Word Embeddings for Cross-lingual Named Entity Recognition	Nov 1, 2017	Cross-Lingual TransferMulti-Task Learning	—Unverified	0
Learning Neural Representations of Human Cognition across Many fMRI Studies	Oct 31, 2017	Dimensionality ReductionMulti-Task Learning	CodeCode Available	0
Multi-Task Learning by Deep Collaboration and Application in Facial Landmark Detection	Oct 28, 2017	Facial Landmark DetectionMulti-Task Learning	CodeCode Available	0
Generalization Tower Network: A Novel Deep Neural Network Architecture for Multi-Task Learning	Oct 27, 2017	Atari GamesMulti-Task Learning	CodeCode Available	0
Bringing Semantic Structures to User Intent Detection in Online Medical Queries	Oct 22, 2017	Intent DetectionMulti-Task Learning	—Unverified	0
Multi-Task Learning for Speaker-Role Adaptation in Neural Conversation Models	Oct 20, 2017	Multi-Task Learning	—Unverified	0

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All datasets QM9 Cityscapes test NYUv2 OMNIGLOT CelebA UTKFace wireframe dataset

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	PCGrad	∆m%	125.7	—	Unverified
2	CAGrad	∆m%	112.8	—	Unverified
3	IMTL-G	∆m%	77.2	—	Unverified
4	Nash-MTL	∆m%	62	—	Unverified
5	BayesAgg-MTL	∆m%	53.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SwinMTL	mIoU	76.41	—	Unverified
2	Nash-MTL	mIoU	75.41	—	Unverified
3	MultiObjectiveOptimization	mIoU	66.63	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SwinMTL	Mean IoU	58.14	—	Unverified
2	Nash-MTL	Mean IoU	40.13	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Gumbel-Matrix Routing	Average Accuracy	93.52	—	Unverified
2	Mixture-of-Experts	Average Accuracy	92.19	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MGDA-UB	Error	8.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BayesAgg-MTL	delta_m	-2.23	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LETR	FH	83.3	—	Unverified