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LemmaStatement: Literature-sourcedProof: AI-adaptedPipeline-generated
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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.

Deviation of local-SGD workers from their virtual mean

Statement

Let T,K,m≥1 be integers and let local SGD use integer synchronization times 0=t0<t1<⋯<tm=T, with H=max⁡j(tj−tj−1). Let xˉt=K−1∑kxtk. For each 0≤t<T, define the previous synchronization time s(t)=max⁡{tj:0≤j≤m, tj≤t}. Suppose the step sizes η0,…,ηT−1 are positive and nonincreasing, and ηs(t)≤2ηt for each 0≤t<T. Suppose also E∥ghk(xhk)∥22≤G2(0≤h<T, 1≤k≤K), where ghk is the local batch gradient. Then, for every 0≤t<T, 1K∑k=1KE∥xtk−xˉt∥22≤4ηt2G2H2. At t=T, the average deviation is zero because T=tm is a synchronization time.

Facts & Assumptions

Given: The local-SGD trajectories, synchronization schedule and local gradient second-moment bound in the Statement.

[F1]

Local SGD with periodic synchronization: all workers have the same iterate at each synchronization time, including the initial time 0.

[F2]

Relaxed inequalities for squared Euclidean norms: squared norms of finite vector sums obey the stated relaxed inequality.

[F3]

Expectation of a nonnegative or integrable random variable: expectation is taken over the finite product law of the sampled indices.

Proof

1.1F1F3givenalgebra

Fix t and let s=s(t) be the latest synchronization time not exceeding [given] t. Then 0≤t−s≤H and [F1] gives xsk=xˉs for all k. For any vectors z1,…,zK and any z, expansion around their mean gives 1K∑k∥zk−zˉ∥22=1K∑k∥zk−z∥22−∥zˉ−z∥22≤1K∑k∥zk−z∥22. Apply this identity with zk=xtk and the common value z=xsk to bound the worker deviation by the mean squared displacement from time s.

1.2F1F2F3step 1.1givenalgebra∎

For each worker, [given] xtk−xsk=−∑h=st−1ηhghk(xhk). By [F2], nonincreasing step sizes, and the second-moment hypothesis, E∥xtk−xsk∥22≤(t−s)∑h=st−1ηh2E∥ghk(xhk)∥22≤H2ηs2G2. Average over k and use ηs≤2ηt from the Statement. The resulting bound is 4H2ηt2G2, proving the claim.

Depends on

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Sources