f(θ) = ½ θᵀHθ
θ⋆
κ(H) ≫ 1
gradient descent
momentum
∇θ L(θ)
x ∈ ℝⁿ
hθ
Mθ = { hθ(x) : x ∈ X }
∂hθ / ∂z₁
∂hθ / ∂z₂
hθ(x₀)
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machine-learning
From Least Squares to Bayesian Linear Regression: A Glance at Bayesian Machine Learning
Aug 11, 2026
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