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 1801–1825 of 3687 papers

TitleStatusHype
In Situ Answer Sentence Selection at Web-scale—0
A Unified Analysis of Multi-task Functional Linear Regression Models with Manifold Constraint and Composite Quadratic Penalty—0
InLINE: Inner-Layer Information Exchange for Multi-task Learning on Heterogeneous Graphs—0
Injecting Imbalance Sensitivity for Multi-Task Learning—0
Deep Mixture of Diverse Experts for Large-Scale Visual Recognition—0
Learning to Transfer via Modelling Multi-level Task Dependency—0
Information Transfer in Multi-Task Learning—0
Learning Twofold Heterogeneous Multi-Task by Sharing Similar Convolution Kernel Pairs—0
Deeply Learned Attributes for Crowded Scene Understanding—0
A Multi-modal Fusion Framework Based on Multi-task Correlation Learning for Cancer Prognosis Prediction—0
Infinite-Task Learning with RKHSs—0
Infinite Shift-invariant Grouped Multi-task Learning for Gaussian Processes—0
Deep Learning for Automatic Quality Grading of Mangoes: Methods and Insights—0
Audio-Visual Speech Inpainting with Deep Learning—0
Left Ventricle Segmentation and Quantification from Cardiac Cine MR Images via Multi-task Learning—0
Infinite Latent SVM for Classification and Multi-task Learning—0
Better transfer learning with inferred successor maps—0
Inferential Text Generation with Multiple Knowledge Sources and Meta-Learning—0
Deep Learning Enabled Segmentation, Classification and Risk Assessment of Cervical Cancer—0
Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks—0
A Multi-modal and Multi-task Learning Method for Action Unit and Expression Recognition—0
A Deep Learning Method for Real-time Bias Correction of Wind Field Forecasts in the Western North Pacific—0
Let the Model Decide its Curriculum for Multitask Learning—0
Leveraging Code Generation to Improve Code Retrieval and Summarization via Dual Learning—0
Achieving RGB-D level Segmentation Performance from a Single ToF Camera—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