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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 3271–3280 of 3687 papers

Title	Date	Tasks	Status	Hype
Gradient Adversarial Training of Neural Networks	Jun 21, 2018	BIG-bench Machine LearningBinary Classification	—Unverified	0
Dynamic Multi-Level Multi-Task Learning for Sentence Simplification	Jun 19, 2018	Multi-Task LearningParaphrase Generation	—Unverified	0
Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Network	Jun 19, 2018	AnatomyMulti-Task Learning	CodeCode Available	0
Fast Multiple Landmark Localisation Using a Patch-based Iterative Network	Jun 18, 2018	Multi-Task Learning	CodeCode Available	0
GILE: A Generalized Input-Label Embedding for Text Classification	Jun 16, 2018	ClassificationGeneral Classification	CodeCode Available	0
A Unified Framework for Generalizable Style Transfer: Style and Content Separation	Jun 13, 2018	DecoderMulti-Task Learning	CodeCode Available	0
Unsupervised Meta-Learning for Reinforcement Learning	Jun 12, 2018	Meta-LearningMeta Reinforcement Learning	—Unverified	0
Multi-Task Neural Models for Translating Between Styles Within and Across Languages	Jun 12, 2018	Machine TranslationMulti-Task Learning	CodeCode Available	0
Multi-Task Deep Networks for Depth-Based 6D Object Pose and Joint Registration in Crowd Scenarios	Jun 11, 2018	3D Pose EstimationMulti-Task Learning	—Unverified	0
Multi-task learning of daily work and study round-trips from survey data	Jun 11, 2018	Decision MakingMulti-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