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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 2751–2760 of 3687 papers

Title	Date	Tasks	Status	Hype
Constructing Multiple Tasks for Augmentation: Improving Neural Image Classification With K-means Features	Nov 18, 2019	ClusteringData Augmentation	CodeCode Available	0
Multi-task Sentence Encoding Model for Semantic Retrieval in Question Answering Systems	Nov 18, 2019	intent-classificationIntent Classification	—Unverified	0
Multi-Task Learning of Height and Semantics from Aerial Images	Nov 18, 2019	Multi-Task Learning	CodeCode Available	0
Forgetting to learn logic programs	Nov 15, 2019	Inductive logic programmingMulti-Task Learning	CodeCode Available	1
Bootstrapping NLU Models with Multi-task Learning	Nov 15, 2019	General ClassificationMulti-Task Learning	—Unverified	0
Simplified and Unified Analysis of Various Learning Problems by Reduction to Multiple-Instance Learning	Nov 14, 2019	Generalization BoundsMulti-Label Learning	CodeCode Available	0
Deep Multi-task Prediction of Lung Cancer and Cancer-free Progression from Censored Heterogenous Clinical Imaging	Nov 12, 2019	Computed Tomography (CT)Diagnostic	—Unverified	0
A Syntax-aware Multi-task Learning Framework for Chinese Semantic Role Labeling	Nov 12, 2019	Chinese Semantic Role LabelingMulti-Task Learning	CodeCode Available	0
Learning Sparse Sharing Architectures for Multiple Tasks	Nov 12, 2019	Multi-Task Learning	CodeCode Available	0
Graph Representation Learning via Multi-task Knowledge Distillation	Nov 11, 2019	Graph Representation LearningKnowledge Distillation	—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