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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 551–560 of 3687 papers

Title	Date	Tasks	Status	Hype
Multi-Task Learning with User Preferences: Gradient Descent with Controlled Ascent in Pareto Optimization	Jan 1, 2020	Multi-Task Learning	CodeCode Available	1
Learning from Synthetic Animals	Dec 17, 2019	Domain AdaptationHuman Parsing	CodeCode Available	1
Regularizing Deep Multi-Task Networks using Orthogonal Gradients	Dec 14, 2019	Multi-Task Learning	CodeCode Available	1
CopyMTL: Copy Mechanism for Joint Extraction of Entities and Relations with Multi-Task Learning	Nov 24, 2019	Entity Extraction using GANMulti-Task Learning	CodeCode Available	1
Forgetting to learn logic programs	Nov 15, 2019	Inductive logic programmingMulti-Task Learning	CodeCode Available	1
On the Detection of Digital Face Manipulation	Oct 3, 2019	Binary ClassificationFace Detection	CodeCode Available	1
Encoding Visual Attributes in Capsules for Explainable Medical Diagnoses	Sep 12, 2019	AttributeLung Cancer Diagnosis	CodeCode Available	1
Multi-task Generative Adversarial Learning on Geometrical Shape Reconstruction from EEG Brain Signals	Jul 31, 2019	EEGElectroencephalogram (EEG)	CodeCode Available	1
An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis	Jun 17, 2019	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	1
Emotion-Cause Pair Extraction: A New Task to Emotion Analysis in Texts	Jun 4, 2019	Emotion Cause ExtractionEmotion-Cause Pair Extraction	CodeCode Available	1

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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