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A separating two-homogeneous flow has globally minimizing projection limits
Statement
Assume AC and the full two-homogeneous hypotheses on , : convex differentiable risk with the prescribed derivative bounds, positive two-homogeneity of , the dense-regular-value condition, and the feature-energy assumptions. Let be a Wasserstein gradient flow whose initial support is compact, lies in , and separates from for . If converges weakly as finite measures on to , then the measure viewed on is a global minimizer of over finite nonnegative Borel measures, and .
Statement references
Feature-measure energy and its regularity assumptions
Wasserstein gradient flow for a feature-measure energy
Two-homogeneous measure projection
First variation and optimality over nonnegative measures
A weak two-homogeneous projection limit is stationary on its support
Negative regular sublevels force two-homogeneous projection escape
A homogeneous flow preserves spherical support separation
Facts & Assumptions
Given: AC, the two-homogeneous flow, its separated initial support, and weak convergence of its projections.
AC is inherited by the flow, characteristic, degree and minimum-norm constructions. The Axiom of Choice
A weak two-homogeneous projection limit is stationary: -almost everywhere. A weak two-homogeneous projection limit is stationary on its support
If is not a minimizer, convexity and first-variation optimality give a direction where ; the regular-value hypothesis supplies the compact negative sublevel needed for escape. First variation and optimality over nonnegative measures Negative regular sublevels force two-homogeneous projection escape
Spherical separation is preserved for every finite time, and the support is the image of the initial support under the characteristic map. A homogeneous flow preserves spherical support separation
In the nonoptimal case, positive mass in the negative cone forces the projection to exit every sufficiently small bounded-Lipschitz neighborhood of . Negative regular sublevels force two-homogeneous projection escape
Weak convergence of gives convergence of the feature moment in Hilbert norm and convergence of the regularizer integral. Feature and energy identities for homogeneous projections
Under AC, an equicontinuous family of continuous functions from a compact metric space to a compact interval has compact closure in the uniform topology. Ascoli–Arzelà in the uniform topology for nonempty compact metric domains
Proof
Given: AC, the flow and convergence in the Statement, and [F1]–[F5].
Suppose for contradiction that is not a global minimizer. By [F1] and [F2], vanishes -almost everywhere but is negative at some sphere point. Choose a negative regular sublevel with that point in its interior, as in [F2].
Weak convergence on the compact sphere implies convergence of total masses by testing the constant function. The bounded-Lipschitz unit ball is equicontinuous and uniformly bounded; Arzelà–Ascoli [F6] gives a finite uniform -net for it. Weak convergence controls each member of that finite net, and the convergent masses bound the error from replacing any test by its net representative. Letting proves bounded-Lipschitz convergence. Thus there is after which , where is the escape radius from [F4]. By [F3], the support at separates some spheres and with . For a point , the radial path between these spheres must meet . That support point has positive radius and direction in ; every sufficiently small open neighborhood of it has positive mass, so the negative cone in [F4] has positive mass.
Applying [F4] at time gives with , contradicting the choice of . Thus is a global minimizer.
By [F5], . Since is a minimizer over all finite nonnegative measures, . This proves both conclusions.
Depends on
- Feature-measure energy and its regularity assumptions
- Wasserstein gradient flow for a feature-measure energy
- Two-homogeneous measure projection
- Feature and energy identities for homogeneous projections
- First variation and optimality over nonnegative measures
- A weak two-homogeneous projection limit is stationary on its support
- Negative regular sublevels force two-homogeneous projection escape
- A homogeneous flow preserves spherical support separation
- The global Wasserstein gradient flow exists uniquely and is stable
- The Axiom of Choice
- Ascoli–Arzelà in the uniform topology for nonempty compact metric domains
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Sources
- Lénaïc Chizat and Francis Bach, On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport (standard reference, not scraped)
- Luigi Ambrosio, Nicola Gigli, and Giuseppe Savaré, Gradient Flows in Metric Spaces and in the Space of Probability Measures (standard reference, not scraped)