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Linear Regression With Random Projections

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Figure

Figure 1: Three representative of initial features ϕ (top row) and a sample of a corresponding ran-dom feature ψ (bottom row)
Figure 2: Example of an initial large texture (left), subsampled (middle), and possible recoveryusing regression with random projections (right)
Figure 3: Least squares estimates of f ⋆, using N = 100 data generated from a peaky distribution P(dashed line in top plots), using 40 Brownian motions {ψp} (middle plots) and using 40hat functions {ϕi} (bottom plots)

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