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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 3061–3070 of 3687 papers

Title	Date	Tasks	Status	Hype
Scaling Multi-Domain Dialogue State Tracking via Query Reformulation	Mar 12, 2019	Dialogue State TrackingMulti-domain Dialogue State Tracking	—Unverified	0
Practical Semantic Parsing for Spoken Language Understanding	Mar 11, 2019	Multi-Task LearningQuestion Answering	—Unverified	0
SleepNet: Automated Sleep Analysis via Dense Convolutional Neural Network Using Physiological Time Series	Mar 11, 2019	Multi-Task LearningTime Series	—Unverified	0
Deep CNN-based Multi-task Learning for Open-Set Recognition	Mar 7, 2019	DecoderGeneral Classification	CodeCode Available	0
Representative Task Self-selection for Flexible Clustered Lifelong Learning	Mar 6, 2019	Lifelong learningModel Optimization	—Unverified	0
EdgeStereo: An Effective Multi-Task Learning Network for Stereo Matching and Edge Detection	Mar 5, 2019	Disparity EstimationEdge Detection	—Unverified	0
Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data	Mar 1, 2019	DenoisingGrammatical Error Correction	CodeCode Available	0
Better, Faster, Stronger Sequence Tagging Constituent Parsers	Feb 28, 2019	Multi-Task LearningSentence	CodeCode Available	0
FaceLiveNet+: A Holistic Networks For Face Authentication Based On Dynamic Multi-task Convolutional Neural Networks	Feb 28, 2019	Face VerificationFacial Expression Recognition	—Unverified	0
Learning to Generate Questions by Learning What not to Generate	Feb 27, 2019	Multi-Task LearningQuestion Answering	—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