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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 1791–1800 of 3687 papers

Title	Date	Tasks	Status	Hype
Revisit Multimodal Meta-Learning through the Lens of Multi-Task Learning	Oct 27, 2021	Meta-LearningMulti-Task Learning	CodeCode Available	0
Adversarial Robustness in Multi-Task Learning: Promises and Illusions	Oct 26, 2021	Adversarial RobustnessMulti-Task Learning	CodeCode Available	0
How to transfer algorithmic reasoning knowledge to learn new algorithms?	Oct 26, 2021	Learning to ExecuteMulti-Task Learning	—Unverified	0
Conflict-Averse Gradient Descent for Multi-task Learning	Oct 26, 2021	Multi-Task Learning	CodeCode Available	1
Multi-Faceted Hierarchical Multi-Task Learning for a Large Number of Tasks with Multi-dimensional Relations	Oct 26, 2021	Multi-Task LearningRecommendation Systems	—Unverified	0
Simultaneous Perturbation Method for Multi-Task Weight Optimization in One-Shot Meta-Learning	Oct 25, 2021	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	0
Generalized Multi-Task Learning from Substantially Unlabeled Multi-Source Medical Image Data	Oct 25, 2021	Multi-Task LearningSegmentation	CodeCode Available	1
AutoMTL: A Programming Framework for Automating Efficient Multi-Task Learning	Oct 25, 2021	Multi-Task Learning	CodeCode Available	1
Multi-task Recurrent Neural Networks to Simultaneously Infer Mode and Purpose in GPS Trajectories	Oct 23, 2021	Multi-Task Learning	—Unverified	0
RefRec: Pseudo-labels Refinement via Shape Reconstruction for Unsupervised 3D Domain Adaptation	Oct 21, 2021	Domain AdaptationMulti-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