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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 2701–2750 of 3687 papers

TitleStatusHype
Multi-Task Learning Enhanced Single Image De-RainingCode0
Cross Lingual Cross Corpus Speech Emotion Recognition—0
3D medical image segmentation with labeled and unlabeled data using autoencoders at the example of liver segmentation in CT images—0
Interpretable MTL from Heterogeneous Domains using Boosted Tree—0
Unified Multi-Domain Learning and Data Imputation using Adversarial Autoencoder—0
Adversarial Encoder-Multi-Task-Decoder for Multi-Stage Processes—0
Beyond without Forgetting: Multi-Task Learning for Classification with Disjoint Datasets—0
OccuSeg: Occupancy-aware 3D Instance Segmentation—0
Inducing Optimal Attribute Representations for Conditional GANs—0
AP-MTL: Attention Pruned Multi-task Learning Model for Real-time Instrument Detection and Segmentation in Robot-assisted SurgeryCode0
Cross-modal Multi-task Learning for Graphic Recognition of Caricature Face—0
Multi-task Learning Based Neural Bridging Reference ResolutionCode0
Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing?Code0
Unsupervised and Interpretable Domain Adaptation to Rapidly Filter Tweets for Emergency ServicesCode0
Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognition—0
Bayesian Neural Networks With Maximum Mean Discrepancy RegularizationCode0
Hand-Priming in Object Localization for Assistive Egocentric Vision—0
Multi-task Learning with Multi-head Attention for Multi-choice Reading Comprehension—0
Evolving Losses for Unsupervised Video Representation Learning—0
Leveraging Code Generation to Improve Code Retrieval and Summarization via Dual Learning—0
Multi-Branch Learning for Weakly-Labeled Sound Event Detection—0
Progressive Layered Extraction (PLE): A Novel Multi-Task Learning (MTL) Model for Personalized RecommendationsCode0
The Sample Complexity of Meta Sparse Regression—0
Learning to Walk in the Real World with Minimal Human Effort—0
The Microsoft Toolkit of Multi-Task Deep Neural Networks for Natural Language Understanding—0
Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning—0
MILA: Multi-Task Learning from Videos via Efficient Inter-Frame Attention—0
Multi-Task Siamese Neural Network for Improving Replay Attack Detection—0
Speech Enhancement using Self-Adaptation and Multi-Head Self-Attention—0
Deep Multi-Task Learning via Generalized Tensor Trace Norm—0
Deep Multi-Task Augmented Feature Learning via Hierarchical Graph Neural NetworkCode0
A Simple General Approach to Balance Task Difficulty in Multi-Task Learning—0
Deep Multi-task Multi-label CNN for Effective Facial Attribute Classification—0
Multi-Task Learning by a Top-Down Control Network—0
Analyzing Policy Distillation on Multi-Task Learning and Meta-Reinforcement Learning in Meta-World—0
Related Tasks can Share! A Multi-task Framework for Affective language—0
Facial Affect Recognition in the Wild Using Multi-Task Learning Convolutional NetworkCode0
A study on the role of subsidiary information in replay attack spoofing detection—0
Incorporating Joint Embeddings into Goal-Oriented Dialogues with Multi-Task LearningCode0
Developing Multi-Task Recommendations with Long-Term Rewards via Policy Distilled Reinforcement Learning—0
Multi-task Learning for Speaker Verification and Voice Trigger Detection—0
Multi-task Learning for Voice Trigger Detection—0
Multi-Task Deep Learning: Simultaneous Segmentation and Survival Analysis via Cox Proportional Hazards Regression—0
MT-BioNER: Multi-task Learning for Biomedical Named Entity Recognition using Deep Bidirectional Transformers—0
DeepFL-IQA: Weak Supervision for Deep IQA Feature LearningCode0
Learning to Multi-Task Learn for Better Neural Machine Translation—0
On Identifying Hashtags in Disaster Twitter DataCode0
Task Understanding from Confusing Multi-task Data—0
Pareto Multi-Task LearningCode0
Improved Multi-Stage Training of Online Attention-based Encoder-Decoder Models—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