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Everything about Multi-task learning
Solving multiple machine learning tasks at the same time
Multi-task learning (MTL) is a subfield of machine learning in which multiple learning tasks are solved at the same time, while exploiting commonalities and differences across tasks. This can result in improved learning efficiency and prediction accuracy for the task-specific models, when compared to training the models separately. Inherently, multi-task learning is a multi-objective optimization problem having trade-offs between different tasks. Early versions of MTL were called "hints". Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Multi-task learningA 5-minute orientation
- Skim a recent paper: Neural multi-task learning in drug designInfluential work since 2022
- Pick up a classic book: Second Language Task-Based PerformanceThe most-reprinted book on the subject
- Read the landmark paper: A Survey on Multi-Task LearningCited 2,216 times
- Go sideways: Online machine learningA closely related topic
- Go sideways: Kernel methods for vector outputA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
A Survey on Multi-Task Learning
An overview of multi-task learning
Convex multi-task feature learning
Latent Multi-Task Architecture Learning
Polymer informatics with multi-task learning
Learning Multi-Level Task Groups in Multi-Task Learning
AdaTask: A Task-Aware Adaptive Learning Rate Approach to Multi-Task Learning
Multi-task reinforcement learning in humans
🆕 Influential since 2022
Neural multi-task learning in drug design
Multi-Task Learning for Randomized Controlled Trials
Multi-task learning with graph attention networks for multi-domain task-oriented dialogue systems
AutoSTL: Automated Spatio-Temporal Multi-Task Learning
Heterogeneous Multi-Task Learning With Expert Diversity
📚 Books worth reading
Second Language Task-Based PerformancePeter Skehan · 2018
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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- Regularized least squares Regularized least squares (RLS) is a family of methods for solving the least-squares problem while using regularization to further constrain the resulting…
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