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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 1751–1775 of 3687 papers

TitleStatusHype
Thompson Sampling for Robust Transfer in Multi-Task BanditsCode0
Multi-View Imputation and Cross-Attention Network Based on Incomplete Longitudinal and Multimodal Data for Conversion Prediction of Mild Cognitive ImpairmentCode0
Learning to Teach Fairness-aware Deep Multi-task Learning—0
Deep Multi-Task Models for Misogyny Identification and Categorization on Arabic Social Media—0
Enhanced Knowledge Selection for Grounded Dialogues via Document Semantic Graphs—0
Codec at SemEval-2022 Task 5: Multi-Modal Multi-Transformer Misogynous Meme Classification FrameworkCode0
Evolutionary Multi-Task Injection Testing on Web Application FirewallsCode0
Surround-View Cameras based Holistic Visual Perception for Automated DrivingCode0
Video-Based Frame-Level Facial Analysis of Affective Behavior on Mobile Devices Using EfficientNets—0
Deep Neural Network for Blind Visual Quality Assessment of 4K Content—0
Deep Estimation of Speckle Statistics Parametric Images—0
Learning to Generate Prompts for Dialogue Generation through Reinforcement Learning—0
An Analysis of Selection Bias Issue for Online Advertising—0
Quantitative Stock Investment by Routing Uncertainty-Aware Trading Experts: A Multi-Task Learning Approach—0
A Benchmark for Federated Hetero-Task Learning—0
Reconsidering Learning Objectives in Unbiased Recommendation with Unobserved Confounders—0
Learning Disentangled Representations for Counterfactual Regression via Mutual Information Minimization—0
RMT-Net: Reject-aware Multi-Task Network for Modeling Missing-not-at-random Data in Financial Credit Scoring—0
Enhancing Relation Extraction via Adversarial Multi-task LearningCode0
Compressed Hierarchical Representations for Multi-Task Learning and Task ClusteringCode0
Principle of Relevant Information for Graph SparsificationCode0
Tackling Multiple Tasks with One Single Learning Framework—0
Automatic Expert Selection for Multi-Scenario and Multi-Task Search—0
Acoustic-to-articulatory Speech Inversion with Multi-task Learning—0
Selective Inference for Sparse Multitask Regression with Applications in Neuroimaging—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