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Partial one-homogeneous energy is continuous under W2 convergence
Statement
Assume AC. Let be a separable real Hilbert space, let be continuous, and let be closed and convex. Let and be bounded Lipschitz maps, and set and . Here means the Borel probability measures on concentrated on and having finite second moment. For every such law define the lower-regularity energy by These integrals exist and is finite. If and , then . Whenever the same data also satisfy the full hypotheses of the feature-measure energy definition, this formula agrees with that definition's on these laws. The present continuity assertion does not require those additional domain or differentiability hypotheses.
Statement references
Facts & Assumptions
Given: The model and W2-convergent laws in the Statement.
AC supplies a sequence of couplings whose quadratic costs approach the W2 infimum. The Axiom of Choice
W2 is the infimum of quadratic coupling costs, so couplings can be chosen with RMS displacement tending to zero. The Euclidean quadratic Wasserstein space
The coupling marginals are the pushforwards under the coordinate projections, so the scalar integral identity follows first for simple functions and then by approximation. For Bochner feature integrals, apply bounded linear functionals, commute them with the Bochner integral, and identify the resulting vectors by all scalar evaluations. The Euclidean quadratic Wasserstein space Bounded linear maps commute with Bochner integration
A strongly measurable function is Bochner integrable exactly when its norm is integrable. Bochner integrability criterion
The Bochner integral is linear and its norm is at most the integral of the pointwise norm. Linearity of the Bochner integral Bochner integral norm inequality
For data satisfying its full hypotheses, the feature-energy definition uses the same risk of the Bochner feature moment plus the integrated penalty whenever both integrals are finite. Feature-measure energy and its regularity assumptions
Proof
Given: and [A1], [F1]–[F4].
First, is Borel measurable with values in the separable space . Fix a countable dense sequence in ; the map assigning to a nearest point among , breaking ties by least index, is finite-valued and measurable, and its error tends to zero as . Thus is strongly measurable. Moreover, . A probability law with finite second moment has by Cauchy–Schwarz. Thus [F3] gives existence of its feature moment, while gives a finite penalty; is finite-valued. This proves the asserted well-definedness for every law in the Statement. By [A1] and [F1] choose couplings of and with . By [F2], the coupling marginal identities hold also for these Bochner feature integrals: apply a bounded linear functional, use the scalar marginal identity, and identify the vectors by all such evaluations. Consequently [F4] and the pointwise bound give The second-moment factor belongs to the fixed limit marginal and is finite, with no bound on the diameter or interior of required.
Since , the same estimate with scalar in place of gives . Step 1.1 gives convergence of feature moments in ; continuity of therefore gives convergence of the risk terms. Adding the two limits proves . Under the full feature-energy hypotheses, the identical feature and penalty integrals are finite by step 1.1, so the finite branch in that definition gives exactly this . If , no law in the Statement exists and the assertion is vacuous; zero maps, zero weights and singleton or lower-dimensional are included in the estimates.
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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)