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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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3376–3400 of 3687 papers

TitleStatusHype
3D Hand Pose and Shape Estimation from RGB Images for Keypoint-Based Hand Gesture Recognition—0
Curriculum Learning for Multi-Task Classification of Visual Attributes—0
Curriculum Based Multi-Task Learning for Parkinson's Disease Detection—0
Efficient Deweather Mixture-of-Experts with Uncertainty-aware Feature-wise Linear Modulation—0
CUNI systems for WMT21: Multilingual Low-Resource Translation for Indo-European Languages Shared Task—0
Efficient Extraction of Pathologies from C-Spine Radiology Reports using Multi-Task Learning—0
Efficient Image Gallery Representations at Scale Through Multi-Task Learning—0
Efficient Image-Text Retrieval via Keyword-Guided Pre-Screening—0
STAN: Stage-Adaptive Network for Multi-Task Recommendation by Learning User Lifecycle-Based Representation—0
Efficient Low-Resolution Face Recognition via Bridge Distillation—0
Efficiently Identifying Task Groupings for Multi-Task Learning—0
Efficient Meta Lifelong-Learning with Limited Memory—0
Star+: A New Multi-Domain Model for CTR Prediction—0
Vehicle Instance Segmentation from Aerial Image and Video Using a Multi-Task Learning Residual Fully Convolutional Network—0
Stem-driven Language Models for Morphologically Rich Languages—0
Efficient Multi-task Prompt Tuning for Recommendation—0
Efficient Multi-task Uncertainties for Joint Semantic Segmentation and Monocular Depth Estimation—0
Efficient Output Kernel Learning for Multiple Tasks—0
Efficient Pairwise Learning Using Kernel Ridge Regression: an Exact Two-Step Method—0
Efficient Pareto Manifold Learning with Low-Rank Structure—0
Efficient Reinforcement Learning in Resource Allocation Problems Through Permutation Invariant Multi-task Learning—0
A Game-Theoretic Perspective of Generalization in Reinforcement Learning—0
Efficient Residual Learning with Mixture-of-Experts for Universal Dexterous Grasping—0
Efficient Retrieval Optimized Multi-task Learning—0
Efficient Task Grouping Through Samplewise Optimisation Landscape Analysis—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