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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 2071–2080 of 3687 papers

Title	Date	Tasks	Status	Hype
OCHADAI-KYOTO at SemEval-2021 Task 1: Enhancing Model Generalization and Robustness for Lexical Complexity Prediction	May 12, 2021	Lexical Complexity PredictionMulti-Task Learning	—Unverified	0
Development of a Multi-Task Learning V-Net for Pulmonary Lobar Segmentation on Computed Tomography and Application to Diseased Lungs	May 11, 2021	Multi-Task LearningSegmentation	—Unverified	0
Differentially Private Transferrable Deep Learning with Membership-Mappings	May 10, 2021	Deep LearningMulti-Task Learning	—Unverified	0
You Only Learn One Representation: Unified Network for Multiple Tasks	May 10, 2021	Multi-Task LearningObject Detection	CodeCode Available	1
Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study	May 8, 2021	Action Unit DetectionAttribute	—Unverified	0
SpeechNet: A Universal Modularized Model for Speech Processing Tasks	May 7, 2021	Multi-Task Learning	CodeCode Available	1
Joint Registration and Segmentation via Multi-Task Learning for Adaptive Radiotherapy of Prostate Cancer	May 5, 2021	Image RegistrationMedical Image Analysis	—Unverified	0
Nonparametric Trace Regression in High Dimensions via Sign Series Representation	May 4, 2021	compressed sensingMatrix Completion	—Unverified	0
Scaling End-to-End Models for Large-Scale Multilingual ASR	Apr 30, 2021	Multi-Task Learning	—Unverified	0
Out-of-Scope Domain and Intent Classification through Hierarchical Joint Modeling	Apr 30, 2021	ClassificationGeneral Classification	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