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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 1941–1950 of 3687 papers

Title	Date	Tasks	Status	Hype
Learning Multi-Tasks with Inconsistent Labels by using Auxiliary Big Task	Jan 7, 2022	Multi-Task Learning	—Unverified	0
Aerial Scene Parsing: From Tile-level Scene Classification to Pixel-wise Semantic Labeling	Jan 6, 2022	Aerial Scene ClassificationBenchmarking	—Unverified	0
How Infinitely Wide Neural Networks Can Benefit from Multi-task Learning -- an Exact Macroscopic Characterization	Dec 31, 2021	Gaussian ProcessesL2 Regularization	CodeCode Available	0
Over-the-Air Federated Multi-Task Learning Over MIMO Multiple Access Channels	Dec 27, 2021	Federated LearningMulti-Task Learning	—Unverified	0
Database Search Results Disambiguation for Task-Oriented Dialog Systems	Dec 15, 2021	Multi-Task Learning	—Unverified	0
Traffic Accident Risk Prediction via Multi-View Multi-Task Spatio-Temporal Networks	Dec 15, 2021	Multi-Task LearningPrediction	CodeCode Available	0
Multi-treatment Effect Estimation from Biomedical Data	Dec 14, 2021	Multi-Task Learning	CodeCode Available	0
ST-MTL: Spatio-Temporal Multitask Learning Model to Predict Scanpath While Tracking Instruments in Robotic Surgery	Dec 10, 2021	Computational EfficiencyMulti-Task Learning	CodeCode Available	0
MTLTS: A Multi-Task Framework To Obtain Trustworthy Summaries From Crisis-Related Microblogs	Dec 10, 2021	Multi-Task LearningRumour Detection	CodeCode Available	0
Findings on Conversation Disentanglement	Dec 10, 2021	Conversational Question AnsweringConversation Disentanglement	—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