Unverified60% confidenceFactExact time
The parameter update rule for gradient descent is θ_{t+1} = θ_t - η·∇L(θ_t), where η is the learning rate, and updating parameters in the direction of the negative gradient reduces the loss function most rapidly.
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60%
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8/23/2026
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