Quiz 2

SGD Variants

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# SGD Variants ## Momentum $v_{t+1} = \beta v_t + \nabla L(\theta_t)$ $\theta_{t+1} = \theta_t - \eta v_{t+1}$ ## Adam (Adaptive Moment Estimation) Combines momentum + adaptive learning rates. Default: $\beta_1 = 0.9, \beta_2 = 0.999$.

SGD Variants

Momentum

vt+1=βvt+∇L(θt)v_{t+1} = \beta v_t + \nabla L(\theta_t) θt+1=θt−ηvt+1\theta_{t+1} = \theta_t - \eta v_{t+1}

Adam (Adaptive Moment Estimation)

Combines momentum + adaptive learning rates. Default: β1=0.9,β2=0.999\beta_1 = 0.9, \beta_2 = 0.999. Join Discord PreviousGradient DescentNextEM Algorithm
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