How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Feature and energy identities for homogeneous projections
Statement
Let , let be a real Hilbert space, let be continuous, and let and be continuous and positively two-homogeneous. For a finite nonnegative Borel measure on with finite second moment, define the feature-measure energy The integrals are finite because the continuous two-homogeneous maps grow at most quadratically. For every such ,
If is a sequence of such measures and converges weakly as finite measures on the compact sphere to a finite nonnegative measure , then the feature integrals converge in Hilbert norm, the regularizer integrals converge, and . The continuity of is the risk premise used for this energy conclusion; it holds in particular under the feature-energy hypotheses.
For the partially one-homogeneous model, let be a closed Euclidean subset, let be bounded and norm-continuous into a separable real Hilbert space, and let be bounded and measurable. Put and . For every finite nonnegative Borel measure on with and every , the exact feature identity is using the scalar pairing defined in the partial projection, and the penalty inequality is . Define the lifted energy in this model by . If finite signed projections converge narrowly to , meaning convergence against every bounded continuous real test on , then their feature moments converge weakly in when is bounded and continuous. If AC holds, then for closed Euclidean and bounded norm-continuous into a separable Hilbert space, they converge in Hilbert norm. Signed projection convergence alone does not imply penalty or full energy convergence for arbitrary lifts.
Statement references
Facts & Assumptions
Given: The two projection definitions and the hypotheses in the Statement.
is a finite measure on . Two-homogeneous measure projection
For every bounded measurable scalar , the projection pairing is , and is a finite signed measure. Partially one-homogeneous signed measure projection
A bounded linear map commutes with Bochner integration, so equality of all scalar evaluations by elements of determines equality of the Hilbert-valued integrals. Bounded linear maps commute with Bochner integration
Under AC, signed narrow convergence on a closed Euclidean subset controls bounded norm-continuous Bochner moments in norm. Signed narrow convergence controls variation tails and Bochner moments The Axiom of Choice
Proof
Given: The measures and feature maps in the Statement.
On , write . Positive two-homogeneity gives and ; at both vanish. Integrating these identities and applying the definition of proves both displayed projection identities.
For weak convergence on the compact sphere, the masses are bounded. The continuous map has compact image in . Given , choose finitely many vectors whose open -balls cover that image and put . Define when the complement is nonempty, and when . The continuous functions are well-defined because the finite open sets cover the sphere, and only when . Therefore uniformly. Weak convergence gives convergence of each scalar coefficient , hence strong convergence of the approximating vector integrals. The uniform approximation error is at most times the uniformly bounded masses, so in norm. Since is continuous, weak convergence also gives . Continuity of proves the energy limit.
If , the only finite measures on and are zero, so all partial feature moments and penalties vanish and all asserted convergence conclusions hold directly. Otherwise is nonempty. In this case, fix and apply [F2] to the bounded scalar function . This gives the displayed feature identity for every , hence equality of the Hilbert-valued feature moments because inner products determine vectors. For the penalty, , and [F2] applied to gives If converges against bounded continuous scalar tests, testing against for each proves weak convergence of the feature moments. Under the additional AC, closed-Euclidean, separable-Hilbert assumptions in the Statement, [F4] improves this to norm convergence. For the claimed failure of penalty determination, take any nonempty and fix . Let assign mass one to and let assign mass two to and mass one to . Then both have equal to the measure assigning mass one to , while their penalties for are and , respectively. Thus convergence alone cannot imply penalty or energy convergence.
Depends on
Used by
- A W2 limit in the two-homogeneous case is globally minimizing Corollary
- A weak two-homogeneous projection limit is stationary on its support Lemma
- Negative regular sublevels force two-homogeneous projection escape Lemma
- A separating two-homogeneous flow has globally minimizing projection limits Theorem
Dependency tree · two levels
24 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
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)