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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 2131–2140 of 3687 papers

Title	Date	Tasks	Status	Hype
Learning Rates for Multi-task Regularization Networks	Apr 1, 2021	BIG-bench Machine LearningMulti-Task Learning	—Unverified	0
Facial expression and attributes recognition based on multi-task learning of lightweight neural networks	Mar 31, 2021	Emotion ClassificationEmotion Recognition	—Unverified	0
Facial expression and attributes recognition based on multi-task learning of lightweight neural networks	Mar 31, 2021	Emotion ClassificationFace Identification	—Unverified	0
High-Dimensional Bayesian Optimization with Multi-Task Learning for RocksDB	Mar 30, 2021	Bayesian OptimizationDimensionality Reduction	—Unverified	0
Target Speaker Verification with Selective Auditory Attention for Single and Multi-talker Speech	Mar 30, 2021	Multi-Task LearningSpeaker Verification	CodeCode Available	1
Autocorrect in the Process of Translation -- Multi-task Learning Improves Dialogue Machine Translation	Mar 30, 2021	Machine TranslationMulti-Task Learning	CodeCode Available	0
CaSiNo: A Corpus of Campsite Negotiation Dialogues for Automatic Negotiation Systems	Mar 29, 2021	Multi-Task LearningPersuasion Strategies	CodeCode Available	1
PeaceGAN: A GAN-based Multi-Task Learning Method for SAR Target Image Generation with a Pose Estimator and an Auxiliary Classifier	Mar 29, 2021	Image GenerationMulti-Task Learning	—Unverified	0
Self-Supervised Learning in Multi-Task Graphs through Iterative Consensus Shift	Mar 26, 2021	Domain AdaptationMulti-Task Learning	CodeCode Available	0
Supervised Chorus Detection for Popular Music Using Convolutional Neural Network and Multi-task Learning	Mar 26, 2021	Multi-Task Learning	—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