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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 3051–3060 of 3687 papers

Title	Date	Tasks	Status	Hype
Veritatem Dies Aperit- Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach	Mar 26, 2019	Autonomous DrivingDepth Completion	CodeCode Available	0
Predicting Multiple Demographic Attributes with Task Specific Embedding Transformation and Attention Network	Mar 25, 2019	AttributeDecision Making	CodeCode Available	0
Towards automatic construction of multi-network models for heterogeneous multi-task learning	Mar 21, 2019	Atari GamesMulti-Task Learning	—Unverified	0
Multi-Task Time Series Analysis applied to Drug Response Modelling	Mar 21, 2019	Multi-Task LearningTime Series	—Unverified	0
Deep Octonion Networks	Mar 20, 2019	General Classificationimage-classification	—Unverified	0
Natural Language Generation at Scale: A Case Study for Open Domain Question Answering	Mar 19, 2019	DecoderKnowledge Graphs	—Unverified	0
MUSEFood: Multi-sensor-based Food Volume Estimation on Smartphones	Mar 18, 2019	ManagementMulti-Task Learning	CodeCode Available	0
Knowledge-aware Complementary Product Representation Learning	Mar 16, 2019	Multi-Task LearningRecommendation Systems	—Unverified	0
Imbalanced multi-label classification using multi-task learning with extractive summarization	Mar 16, 2019	ClassificationExtractive Summarization	CodeCode Available	0
Few-Shot and Zero-Shot Learning for Historical Text Normalization	Mar 12, 2019	LemmatizationMulti-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