A global minimizer is a point attaining the infimum of an objective. For an extended-real functional, it is usual to require a finite objective value; this excludes points outside its effective domain. A convention allowing +∞ as the attained value gives every point as a formal minimizer of the identically infinite function.
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- Affine Euler-Lagrange solution from finite derivative fibers
- Alternating proximal-gradient operator
- Approximation property of an infimum
- Averaged stationarity bound for stochastic gradient descent
- Exact line search
- Global minimizer
- Global minimum
- Infimum and supremum
- KKT point
- Local minimizer
- Minimizing sequence
- Monotonicity of data fidelity and regularization penalty
- Nesterov accelerated gradient method
- Parameter continuity of variational regularization
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- Proximal gradient mapping
- Proximal gradient objective error bound
- Strong convexity gradient inequality
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