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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 3531–3540 of 3687 papers

Title	Date	Tasks	Status	Hype
A multi-task learning model for malware classification with useful file access pattern from API call sequence	Oct 19, 2016	ClassificationDocument Classification	—Unverified	0
Neural Joint Learning for Classifying Wikipedia Articles into Fine-grained Named Entity Types	Oct 1, 2016	ArticlesEntity Linking	—Unverified	0
融合多任務學習類神經網路聲學模型訓練於會議語音辨識之研究(Leveraging Multi-task Learning with Neural Network Based Acoustic Modeling for Improved Meeting Speech Recognition) [In Chinese]	Oct 1, 2016	Multi-Task Learningspeech-recognition	—Unverified	0
Asynchronous Multi-Task Learning	Sep 30, 2016	Multi-Task LearningTransfer Learning	CodeCode Available	0
Learning to Push by Grasping: Using multiple tasks for effective learning	Sep 28, 2016	Multi-Task Learning	—Unverified	0
Deep Multi-Task Learning with Shared Memory	Sep 23, 2016	General ClassificationMulti-Task Learning	—Unverified	0
Joint CTC-Attention based End-to-End Speech Recognition using Multi-task Learning	Sep 21, 2016	DecoderMulti-Task Learning	CodeCode Available	0
DeepSkeleton: Learning Multi-task Scale-associated Deep Side Outputs for Object Skeleton Extraction in Natural Images	Sep 13, 2016	Multi-Task LearningObject	CodeCode Available	0
Using Gaussian Processes for Rumour Stance Classification in Social Media	Sep 7, 2016	Gaussian ProcessesGeneral Classification	—Unverified	0
Ask the GRU: Multi-Task Learning for Deep Text Recommendations	Sep 7, 2016	ArticlesCollaborative Filtering	—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