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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

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Showing 2401–2425 of 3687 papers

TitleStatusHype
Learnable Dependency-based Double Graph Structure for Aspect-based Sentiment Analysis—0
Robust and flexible learning of a high-dimensional classification rule using auxiliary outcomes—0
Learning quantum properties from short-range correlations using multi-task networks—0
Learning an Interpretable Graph Structure in Multi-Task Learning—0
Learning Answer-Entailing Structures for Machine Comprehension—0
Learning attention for historical text normalization by learning to pronounce—0
Learning-based Bone Quality Classification Method for Spinal Metastasis—0
Learning behavioral context recognition with multi-stream temporal convolutional networks—0
Learning Boost by Exploiting the Auxiliary Task in Multi-task Domain—0
Learning Cancer Outcomes from Heterogeneous Genomic Data Sources: An Adversarial Multi-task Learning Approach—0
Learning Cross-Task Attribute - Attribute Similarity for Multi-task Attribute-Value Extraction—0
Learning curves for multi-task Gaussian process regression—0
Learning Disentangled Representations for Counterfactual Regression via Mutual Information Minimization—0
Learning distributed event representations with a multi-task approach—0
Learning Domain Representation for Multi-Domain Sentiment Classification—0
Learning Feature Selection Dependencies in Multi-task Learning—0
Learning Flexible Translation between Robot Actions and Language Descriptions—0
Learning from Auxiliary Sources in Argumentative Revision Classification—0
Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization—0
Learning from Multiway Data: Simple and Efficient Tensor Regression—0
Learning from Synthetic Data: Facial Expression Classification based on Ensemble of Multi-task Networks—0
Learning Gaussian Maps for Dense Object Detection—0
Learning heuristics for A*—0
Learning More for Free - A Multi Task Learning Approach for Improved Pathology Classification in Capsule Endoscopy—0
Learning Multiple Tasks with Multilinear Relationship Networks—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