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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 1431–1440 of 3687 papers

Title	Date	Tasks	Status	Hype
Noise-aware Physics-informed Machine Learning for Robust PDE Discovery	Jun 26, 2022	BIG-bench Machine LearningDenoising	CodeCode Available	0
Burst2Vec: An Adversarial Multi-Task Approach for Predicting Emotion, Age, and Origin from Vocal Bursts	Jun 24, 2022	Multi-Task Learning	CodeCode Available	0
SAQAM: Spatial Audio Quality Assessment Metric	Jun 24, 2022	Audio Quality AssessmentMulti-Task Learning	—Unverified	0
A Manifold-based Airfoil Geometric-feature Extraction and Discrepant Data Fusion Learning Method	Jun 23, 2022	Multi-Task Learning	—Unverified	0
Adversarial Multi-Task Learning for Disentangling Timbre and Pitch in Singing Voice Synthesis	Jun 23, 2022	Generative Adversarial NetworkMulti-Task Learning	—Unverified	0
Multi-task twin support vector machine with Universum data	Jun 22, 2022	Multi-Task Learning	—Unverified	0
Semantics-Depth-Symbiosis: Deeply Coupled Semi-Supervised Learning of Semantics and Depth	Jun 21, 2022	Data AugmentationDepth Estimation	—Unverified	0
Learning Multi-Task Transferable Rewards via Variational Inverse Reinforcement Learning	Jun 19, 2022	Generative Adversarial NetworkImitation Learning	—Unverified	0
Motley: Benchmarking Heterogeneity and Personalization in Federated Learning	Jun 18, 2022	BenchmarkingFairness	CodeCode Available	0
DenseMTL: Cross-task Attention Mechanism for Dense Multi-task Learning	Jun 17, 2022	2D Semantic SegmentationDepth Estimation	CodeCode Available	1

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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