Amazon Science on Mythryl: “Training a graph neural network on multiple objectives usually means…”

Training a graph neural network on multiple objectives usually means blending conflicting gradients at every step. Instead of compromising among parameter updates from different training objectives, ControlG allocates capacity to objectives sequentially and dynamically via PID control. #ICML2026

amazon.scienceHow controllers from industrial machinery can coordinate multitask machine learningInstead of compromising among parameter updates dictated by different training objectives, ControlG allocates computational capacity to objectives sequentially and dynamically.

31/7/26, 7:18 pm0 reposts1 like

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