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

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Showing 1726–1750 of 3687 papers

TitleStatusHype
Deep Multi-Task Learning for Joint Localization, Perception, and Prediction—0
Interpretable Multi-task Learning with Shared Variable Embeddings—0
Dynamic Predictions of Postoperative Complications from Explainable, Uncertainty-Aware, and Multi-Task Deep Neural Networks—0
Deep Multi-task Learning for Facial Expression Recognition and Synthesis Based on Selective Feature Sharing—0
Learning Cancer Outcomes from Heterogeneous Genomic Data Sources: An Adversarial Multi-task Learning Approach—0
A Unified Framework for Campaign Performance Forecasting in Online Display Advertising—0
A Multi-Task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients Using Dynamic Functional Connectivity—0
Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning—0
Interpretable MTL from Heterogeneous Domains using Boosted Tree—0
Learning distributed event representations with a multi-task approach—0
Learning Domain Representation for Multi-Domain Sentiment Classification—0
Interpretable Meta-Learning of Physical Systems—0
Deep Depression Prediction on Longitudinal Data via Joint Anomaly Ranking and Classification—0
Learning Feature Selection Dependencies in Multi-task Learning—0
Learning Flexible Translation between Robot Actions and Language Descriptions—0
Interplay of Machine Translation, Diacritics, and Diacritization—0
Learning from Auxiliary Sources in Argumentative Revision Classification—0
Deep Multi-Task Learning for Cooperative NOMA: System Design and Principles—0
A Unified Framework for Adaptive Representation Enhancement and Inversed Learning in Cross-Domain Recommendation—0
Deep Multi-Task Learning for Aspect Term Extraction with Memory Interaction—0
IntentRec: Predicting User Session Intent with Hierarchical Multi-Task Learning—0
Intent Discovery for Enterprise Virtual Assistants: Applications of Utterance Embedding and Clustering to Intent Mining—0
Deep Multi-Task Learning for Anomalous Driving Detection Using CAN Bus Scalar Sensor Data—0
A Unified Architecture for Semantic Role Labeling and Relation Classification—0
A Multi-Task Architecture on Relevance-based Neural Query Translation—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