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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 3211–3220 of 3687 papers

Title	Date	Tasks	Status	Hype
Convex Learning of Multiple Tasks and their Structure	Apr 13, 2015	Multi-Task Learning	CodeCode Available	0
Revisit Multimodal Meta-Learning through the Lens of Multi-Task Learning	Oct 27, 2021	Meta-LearningMulti-Task Learning	CodeCode Available	0
Stylistic Multi-Task Analysis of Ukiyo-e Woodblock Prints	Oct 16, 2024	Multi-Task Learning	CodeCode Available	0
Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creative	May 17, 2019	Multi-Task LearningPrediction	CodeCode Available	0
A Multi-term and Multi-task Analyzing Framework for Affective Analysis in-the-wild	Sep 29, 2020	Multi-Task Learning	CodeCode Available	0
Which Tasks Should Be Learned Together in Multi-task Learning?	May 18, 2019	Multi-Task Learning	CodeCode Available	0
Multi-View Imputation and Cross-Attention Network Based on Incomplete Longitudinal and Multimodal Data for Conversion Prediction of Mild Cognitive Impairment	Jun 16, 2022	Disease PredictionImputation	CodeCode Available	0
Subspace Network: Deep Multi-Task Censored Regression for Modeling Neurodegenerative Diseases	Feb 19, 2018	Multi-Task Learningregression	CodeCode Available	0
Identifying beneficial task relations for multi-task learning in deep neural networks	Feb 27, 2017	Multi-Task Learning	CodeCode Available	0
Less is More: Selective Layer Finetuning with SubTuning	Feb 13, 2023	Multi-Task Learning	CodeCode Available	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