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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 2811–2820 of 3687 papers

Title	Date	Tasks	Status	Hype
Flexible Multi-task Networks by Learning Parameter Allocation	Oct 10, 2019	Multi-Task Learning	—Unverified	0
The Sparse Reverse of Principal Component Analysis for Fast Low-Rank Matrix Completion	Oct 4, 2019	Image ReconstructionLow-Rank Matrix Completion	—Unverified	0
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints	Oct 4, 2019	ClusteringFederated Learning	CodeCode Available	0
NeurReg: Neural Registration and Its Application to Image Segmentation	Oct 4, 2019	Image RegistrationImage Segmentation	CodeCode Available	0
Hitachi at MRP 2019: Unified Encoder-to-Biaffine Network for Cross-Framework Meaning Representation Parsing	Oct 3, 2019	DecoderMulti-Task Learning	—Unverified	0
On the Detection of Digital Face Manipulation	Oct 3, 2019	Binary ClassificationFace Detection	CodeCode Available	1
Joint Acne Image Grading and Counting via Label Distribution Learning	Oct 1, 2019	Acne Severity GradingMedical Image Classification	CodeCode Available	0
Learning to Jointly Generate and Separate Reflections	Oct 1, 2019	Multi-Task LearningReflection Removal	—Unverified	0
MMM: Multi-stage Multi-task Learning for Multi-choice Reading Comprehension	Oct 1, 2019	Logical ReasoningMachine Reading Comprehension	CodeCode Available	0
Single-Network Whole-Body Pose Estimation	Sep 30, 2019	Multi-Task LearningPose Estimation	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