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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 2581–2590 of 3687 papers

Title	Date	Tasks	Status	Hype
Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization	Jul 18, 2020	Anomaly DetectionDomain Generalization	—Unverified	0
MTL2L: A Context Aware Neural Optimiser	Jul 18, 2020	Multi-Task Learning	CodeCode Available	0
Audio Tagging by Cross Filtering Noisy Labels	Jul 16, 2020	Audio TaggingMemorization	—Unverified	0
MTP: Multi-Task Pruning for Efficient Semantic Segmentation Networks	Jul 16, 2020	ClassificationGeneral Classification	—Unverified	0
Neural MOS Prediction for Synthesized Speech Using Multi-Task Learning With Spoofing Detection and Spoofing Type Classification	Jul 16, 2020	Multi-Task LearningPrediction	—Unverified	0
Fine-Tune Longformer for Jointly Predicting Rumor Stance and Veracity	Jul 15, 2020	Multi-Task LearningRumour Detection	—Unverified	0
Semi-supervised Learning with a Teacher-student Network for Generalized Attribute Prediction	Jul 14, 2020	AttributeMulti-Task Learning	—Unverified	0
Follow the bisector: a simple method for multi-objective optimization	Jul 14, 2020	imbalanced classificationMulti-Task Learning	CodeCode Available	0
HyperGrid: Efficient Multi-Task Transformers with Grid-wise Decomposable Hyper Projections	Jul 12, 2020	Multi-Task LearningNatural Language Understanding	—Unverified	0
Online Parameter-Free Learning of Multiple Low Variance Tasks	Jul 11, 2020	Meta-LearningMulti-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