FAMO: A Fast Optimization Method for Multitask Learning (MTL) that Mitigates the Conflicting Gradients using O(1) Space and Time

Multitask learning (MLT) involves training a single model to perform multiple tasks simultaneously, leveraging shared information to enhance performance. While beneficial, MLT poses challenges in managing large models and optimizing across tasks. Optimizing the average loss may lead to suboptimal performance if tasks progress unevenly. Balancing task performance and optimization strategies is critical for effective MLT. […]

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