Pengxin-Guo/Awesome-Multi-Task-Learning
Paper List for Multi-Task Learning (focus on architectures and optimization for MTL)
This resource compiles academic papers focusing on Multi-Task Learning (MTL) to help AI/ML researchers and practitioners improve their models. It provides a structured list of research on architectures and optimization methods for MTL, serving as a guide for selecting or designing effective multi-task learning systems. The target audience is machine learning engineers and researchers looking to develop or apply advanced AI models.
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Use this if you are a machine learning researcher or practitioner designing or optimizing models that need to perform multiple related tasks simultaneously.
Not ideal if you are looking for ready-to-use code, tutorials for beginners, or a general overview of machine learning concepts.
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Nov 30, 2023
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