An Overview of Multi-task Learning
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Summary
Many areas, including computer vision, bioinformatics, health informatics, speech, natural language processing, web applications and ubiquitous computing, use MTL to improve the performance of the applications involved and some representative works are reviewed.
- Type
- article
- Published
- 2018-01-01
- Cited by
- 1,929
- References
- 135
- Access
- Open access
- OpenAlex
- https://openalex.org/W2753709519
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:90063862
Keywords
Computer science, Task (project management), Multi-task learning, Artificial intelligence, Unsupervised learning
References
- Multi-Task Learning using Generalized t Process
- Active Multitask Learning Using Both Latent and Supervised Shared Topics
- Learning High-Order Task Relationships in Multi-Task Learning
- Encoding Tree Sparsity in Multi-Task Learning: A Probabilistic Framework
- Convex Multi-Task Learning by Clustering
- A Probabilistic Model for Dirty Multi-task Feature Selection
- Linear Algorithms for Online Multitask Classification
- Deep neural networks employing Multi-Task Learning and stacked bottleneck features for speech synthesis
- Discovering Structure in Multiple Learning Tasks: The TC Algorithm
- A Convex Formulation for Learning Task Relationships in Multi-Task Learning
- Multi-Task CNN Model for Attribute Prediction
- Rotating your face using multi-task deep neural network
- Multi-task deep visual-semantic embedding for video thumbnail selection
- Multi-task Sparse Learning with Beta Process Prior for Action Recognition
- No Matter Where You Are: Flexible Graph-Guided Multi-task Learning for Multi-view Head Pose Classification under Target Motion
- A convex formulation for learning shared structures from multiple tasks
- Multi-task low-rank affinity pursuit for image segmentation
- Learning Tree Structure in Multi-Task Learning
- Convex Discriminative Multitask Clustering
- Integrating low-rank and group-sparse structures for robust multi-task learning
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- A Survey on Multi-Task Learning
- DeepFaceLIFT: Interpretable Personalized Models for Automatic Estimation of Self-Reported Pain
- Curriculum Learning for Multi-task Classification of Visual Attributes
- Multi-task neural networks for personalized pain recognition from physiological signals
- Automatic Detection of Malware-Generated Domains with Recurrent Neural Models
- Regularization for Deep Learning: A Taxonomy
- Multi-modal emotion recognition using semi-supervised learning and multiple neural networks in the wild
- Personalized Driver Stress Detection with Multi-task Neural Networks using Physiological Signals
- Multi-Task Pharmacovigilance Mining from Social Media Posts
- Deep Learning for Genomics: A Concise Overview
- Personalized machine learning for robot perception of affect and engagement in autism therapy
- Constrained Deep Learning using Conditional Gradient and Applications in Computer Vision
- MultiNet: Multi-Modal Multi-Task Learning for Autonomous Driving
- Comparatives, Quantifiers, Proportions: a Multi-Task Model for the Learning of Quantities from Vision
- Not‐so‐supervised: A survey of semi‐supervised, multi‐instance, and transfer learning in medical image analysis
- A Multi-lingual Multi-task Architecture for Low-resource Sequence Labeling
- CNN with coarse-to-fine layer for hierarchical classification
- Auxiliary Tasks in Multi-task Learning
- Multi-Label Transfer Learning for Semantic Similarity
- deepSA2018 at SemEval-2018 Task 1: Multi-task Learning of Different Label for Affect in Tweets
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