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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 3611–3620 of 3687 papers

Title	Date	Tasks	Status	Hype
ECNU: Using Traditional Similarity Measurements and Word Embedding for Semantic Textual Similarity Estimation	Jun 1, 2015	Multi-Task LearningNatural Language Inference	—Unverified	0
Classifying Tweet Level Judgements of Rumours in Social Media	Jun 1, 2015	Domain AdaptationMulti-Task Learning	—Unverified	0
Hyper-Class Augmented and Regularized Deep Learning for Fine-Grained Image Classification	Jun 1, 2015	Fine-Grained Image ClassificationGeneral Classification	—Unverified	0
Automatically Scoring Freshman Writing: A Preliminary Investigation	Jun 1, 2015	Multi-Task Learning	—Unverified	0
Deeply Learned Attributes for Crowded Scene Understanding	Jun 1, 2015	AttributeMulti-Task Learning	—Unverified	0
Deep sparse multi-task learning for feature selection in Alzheimer’s disease diagnosis	May 21, 2015	Clusteringfeature selection	—Unverified	0
Multi-task additive models with shared transfer functions based on dictionary learning	May 19, 2015	Additive modelsDictionary Learning	—Unverified	0
Multi-Task Word Alignment Triangulation for Low-Resource Languages	May 1, 2015	Machine TranslationMulti-Task Learning	—Unverified	0
Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval	May 1, 2015	Domain Adaptationdomain classification	—Unverified	0
Learning Multiple Visual Tasks while Discovering their Structure	Apr 13, 2015	DenoisingGeneral Classification	—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