awesome-multi-task-learning
github.com/simonvandenhende/awesome-multi-task-learning ↗A list of multi-task learning papers and projects.
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23 hours ago
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WorkshopSurvey papersDatasetsArchitecturesNeural Architecture SearchOptimization strategiesTransfer learning & Domain AdaptationRobustnessOther
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Survey papers
Neural Architecture Search
- AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning
- Automated Search for Resource-Efficient Branched Multi-Task Networks
- Branched multi-task networks: deciding what layers to share
- Feature partitioning for efficient multi-task architectures
- Fully-adaptive feature sharing in multi-task networks with applications in person attribute classification
- Learning to Branch for Multi-Task Learning
Optimization strategies
- Adversarial multi-task learning for text classification
- A modulation module for multi-task learning with applications in image retrieval
- Dynamic task prioritization for multitask learning
- Gradient surgery for multi-task learning
- Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks
- Instance-Level Task Parameters: A Robust Multi-task Weighting Framework
Robustness
Architectures
- Attentive single-tasking of multiple tasksOther
- Beyond shared hierarchies: Deep multitask learning through soft layer orderingOther
- Cross-stitch networks for multi-task learningEncoder-based architectures
- Deep multi-task representation learning: A tensor factorisation approachOther
- Efficient parametrization of multi-domain deep neural networksOther
- End-to-end multi-task learning with attentionEncoder-based architectures
Transfer learning & Domain Adaptation
- Large scale fine-grained categorization and domain-specific transfer learning
- Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation
- Representation similarity analysis for efficient task taxonomy & transfer learning
- Task2vec: Task embedding for meta-learning
- Taskonomy: Disentangling task transfer learning
Showing a sample of 66 resources. View the full list on GitHub →