SGD — 2D Loss Landscape Exploration
Stochastic gradient descent navigating a parameterized loss surface
θ_{t+1} = θ_t − η·∇L̃(θ_t) | L̃ = noisy minibatch estimate | Escape rate ∝ e^{−ΔL/η}
Learning rate η
0.01
Batch noise σ
0.10
Momentum β
0.00
Landscape type
Rosenbrock
Rastrigin
Beale
Himmelblau
Pause
Reset
Click landscape to set start point
Loss
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Step
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||grad||
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Position (x,y)
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