SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 876–900 of 3687 papers

TitleStatusHype
Discriminatory Transfer—0
Disentangled Interleaving Variational Encoding—0
Disentangled Latent Spaces Facilitate Data-Driven Auxiliary Learning—0
Deep Learning for Automatic Quality Grading of Mangoes: Methods and Insights—0
Disentangling Representations through Multi-task Learning—0
Disjoint Multi-task Learning between Heterogeneous Human-centric Tasks—0
Distance Correlation Based Brain Functional Connectivity Estimation and Non-Convex Multi-Task Learning for Developmental fMRI Studies—0
A Multi-modal and Multi-task Learning Method for Action Unit and Expression Recognition—0
Distantly Supervised Relation Extraction with Sentence Reconstruction and Knowledge Base Priors—0
Distillation based Multi-task Learning: A Candidate Generation Model for Improving Reading Duration—0
Distill Knowledge in Multi-task Reinforcement Learning with Optimal-Transport Regularization—0
Distributed Deep Reinforcement Learning: An Overview—0
Distributed Multitask Learning—0
Distributed Multi-Task Learning for Stochastic Bandits with Context Distribution and Stage-wise Constraints—0
Distributed Multi-Task Learning with Shared Representation—0
Distributed Multi-Task Relationship Learning—0
Distributed Networked Multi-task Learning—0
Distributed Primal-Dual Optimization for Online Multi-Task Learning—0
Distributed Stochastic Multi-Task Learning with Graph Regularization—0
Deep Learning Enabled Segmentation, Classification and Risk Assessment of Cervical Cancer—0
Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks—0
Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study—0
Distribution Matching for Multi-Task Learning of Classification Tasks: a Large-Scale Study on Faces & Beyond—0
3D medical image segmentation with labeled and unlabeled data using autoencoders at the example of liver segmentation in CT images—0
English Conversational Telephone Speech Recognition by Humans and Machines—0
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All datasetsQM9Cityscapes testNYUv2OMNIGLOTCelebAUTKFacewireframe dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PCGrad∆m%125.7—Unverified
2CAGrad∆m%112.8—Unverified
3IMTL-G∆m%77.2—Unverified
4Nash-MTL∆m%62—Unverified
5BayesAgg-MTL∆m%53.7—Unverified
#ModelMetricClaimedVerifiedStatus
1SwinMTLmIoU76.41—Unverified
2Nash-MTLmIoU75.41—Unverified
3MultiObjectiveOptimizationmIoU66.63—Unverified
#ModelMetricClaimedVerifiedStatus
1SwinMTLMean IoU58.14—Unverified
2Nash-MTLMean IoU40.13—Unverified
#ModelMetricClaimedVerifiedStatus
1Gumbel-Matrix RoutingAverage Accuracy93.52—Unverified
2Mixture-of-ExpertsAverage Accuracy92.19—Unverified
#ModelMetricClaimedVerifiedStatus
1MGDA-UBError8.25—Unverified
#ModelMetricClaimedVerifiedStatus
1BayesAgg-MTLdelta_m-2.23—Unverified
#ModelMetricClaimedVerifiedStatus
1LETRFH83.3—Unverified