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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 891–900 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Multi-Task Learning Enhanced Single Image De-Raining	Mar 21, 2020	Multi-Task LearningRain Removal	CodeCode Available	0	5
Multi-task Learning for Aggregated Data using Gaussian Processes	Jun 22, 2019	Air Pollution PredictionEpidemiology	CodeCode Available	0	5
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes	Apr 10, 2017	Bayesian Inferencecounterfactual	CodeCode Available	0	5
Cross-Task Consistency Learning Framework for Multi-Task Learning	Nov 28, 2021	Contrastive LearningMulti-Task Learning	CodeCode Available	0	5
Ask Question First for Enhancing Lifelong Language Learning	Aug 17, 2022	Language ModelingLanguage Modelling	CodeCode Available	0	5
iCAR: Bridging Image Classification and Image-text Alignment for Visual Recognition	Apr 22, 2022	Action RecognitionClassification	CodeCode Available	0	5
Cross-stitch Networks for Multi-task Learning	Apr 12, 2016	Multi-Task LearningSemantic Segmentation	CodeCode Available	0	5
Hyperparameter Auto-tuning in Self-Supervised Robotic Learning	Oct 16, 2020	DiversityMulti-Task Learning	CodeCode Available	0	5
Cross-Stitched Multi-task Dual Recursive Networks for Unified Single Image Deraining and Desnowing	Nov 15, 2022	Image RestorationMulti-Task Learning	CodeCode Available	0	5
iCLIP: Bridging Image Classification and Contrastive Language-Image Pre-Training for Visual Recognition	Jan 1, 2023	Classificationimage-classification	CodeCode Available	0	5

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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