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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 3581–3590 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Conversion of single-energy computed tomography to parametric maps of dual-energy computed tomography using convolutional neural network	Sep 26, 2023	Multi-Task Learning	—Unverified	0	0
Surpassing Human-Level Face Verification Performance on LFW with GaussianFace	Apr 15, 2014	DiversityFace Recognition	—Unverified	0	0
SURREY-CTS-NLP at WASSA2022: An Experiment of Discourse and Sentiment Analysis for the Prediction of Empathy, Distress and Emotion	May 1, 2022	ArticlesEnsemble Learning	—Unverified	0	0
Fed-Focal Loss for imbalanced data classification in Federated Learning	Nov 12, 2020	ClassificationFederated Learning	—Unverified	0	0
FedGradNorm: Personalized Federated Gradient-Normalized Multi-Task Learning	Mar 24, 2022	Federated LearningMulti-Task Learning	—Unverified	0	0
Convergence rate of Bayesian tensor estimator: Optimal rate without restricted strong convexity	Aug 13, 2014	Collaborative FilteringMulti-Task Learning	—Unverified	0	0
Visual Exemplar Driven Task-Prompting for Unified Perception in Autonomous Driving	Mar 3, 2023	Autonomous DrivingLane Detection	—Unverified	0	0
FedNILM: Applying Federated Learning to NILM Applications at the Edge	Jun 7, 2021	Federated LearningModel Compression	—Unverified	0	0
Controllable Pareto Multi-Task Learning	Oct 13, 2020	Multiobjective OptimizationMulti-Task Learning	—Unverified	0	0
FewFedWeight: Few-shot Federated Learning Framework across Multiple NLP Tasks	Dec 16, 2022	Federated LearningFew-Shot Learning	—Unverified	0	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