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Paper Citation Record · LEDGER

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift

As of 18 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2506.23453.

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pith.paper-citation-record.v1
2506.23453 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:56:38.803789Z

measured 22 of 22 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

22 of 22 outbound references displayed

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External citation measurements

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Outbound references

Observation 6feefa65-3a7c-46cb-8257-2307caf51f02 · outbound

This paper cites In order to determine the separation between two priors µ0 and µ1, we need to derive the con- centration inequality of each prior first.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift In order to determine the separation between two priors µ0 and µ1, we need to derive the con- centration inequality of each prior first

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 6c6d15de-a800-4360-8ad3-44dcb0b75bf9 · outbound

This paper cites of the uniform distribution over [0, 1]d.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift of the uniform distribution over [0, 1]d

Reference 2

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d9cb1dca-fd75-465f-93c7-55bdd611e4ae · outbound

This paper cites A.5 P ROOF OF COROLLARY 1 Corollary 1 (Double Robustness of Plug-in Truncated Estimator).

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift A.5 P ROOF OF COROLLARY 1 Corollary 1 (Double Robustness of Plug-in Truncated Estimator)

Reference 3

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0c04e898-49d7-4244-a6b8-bde1175c47a8 · outbound

This paper cites Instance weighting for neural machine translation domain adaptation.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift Instance weighting for neural machine translation domain adaptation

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation a361389f-eed9-4ed4-b637-3e9d1af7e279 · outbound

This paper cites an unresolved cited work.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift Unresolved cited work

Reference 10

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7b6872e1-69a2-45e3-b116-e198f5a4c0c5 · outbound

This paper cites Assume that p ≥ 2, q ≤ p ≤ 2q and s d > 1 p − 1 2q.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift Assume that p ≥ 2, q ≤ p ≤ 2q and s d > 1 p − 1 2q

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:56:38.219386Z digest=sha256:313f29278d4778b7cc74e705998d98cf4af4e120a34f44fe746fce8b71aab425

Observation b640e6d5-f911-4633-81b1-e11e975bb19d · outbound

This paper cites This gives us the final upper bound under the assumption that s ∈ ( d(2q−p) p(2q−2) , d p ) as follows: ES1 Z Ω g2 S1 (x)f 2q−2(x) dx ≲ ¯b · n− 2s d.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift This gives us the final upper bound under the assumption that s ∈ ( d(2q−p) p(2q−2) , d p ) as follows: ES1 Z Ω g2 S1 (x)f 2q−2(x) dx ≲ ¯b · n− 2s d

Reference 14

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2e70dd0a-0a45-49fe-997f-7e1c1eb6fc49 · outbound

This paper cites (22) Combining the upper bounds derived in 19 20, 21 and 22 we may deduce that: ES1 ES2|S1 f q(X) − ˆf q S1 (X) 2 ≲ ¯b2 · h n2q( 1 p − s d )−1 + max{n− 2s d , n2q( 1 p − s d )−1} i.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift (22) Combining the upper bounds derived in 19 20, 21 and 22 we may deduce that: ES1 ES2|S1 f q(X) − ˆf q S1 (X) 2 ≲ ¯b2 · h n2q( 1 p − s d )−1 + max{n− 2s d , n2q( 1 p − s d )−1} i

Reference 15

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Observation 2fc3fc5e-3bb5-4035-8c9c-6f4a87fdc86e · outbound

This paper cites Z Ω− T p∗(x) ˆf q S1 (x)dx + Z Ω− T T p◦(x) · (f q(x) − ˆf q S1 (x))dx − Z Ω− T p∗(x)f q(x)dx # =ES1.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift Z Ω− T p∗(x) ˆf q S1 (x)dx + Z Ω− T T p◦(x) · (f q(x) − ˆf q S1 (x))dx − Z Ω− T p∗(x)f q(x)dx # =ES1

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 95d112a6-1223-4b35-a70b-602435a1abf0 · outbound

This paper cites To estimate the propensity score, we can apply a classification model that distinguishes between source and target samples.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift To estimate the propensity score, we can apply a classification model that distinguishes between source and target samples

Reference 18

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 22e52dd3-9e65-4ff9-9f70-e9f4a5f5917e · outbound

This paper cites These potential outcomes are un- known functions of the covariate X.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift These potential outcomes are un- known functions of the covariate X

Reference 19

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f4890b1c-4f8a-4847-9352-6ae17f095e37 · outbound

This paper cites (8) may outperform the minimax lower bound B · ¯b · r(n) when B is large.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift (8) may outperform the minimax lower bound B · ¯b · r(n) when B is large

Reference 20

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Observation d0fe20f7-3753-43f0-9754-d79ff813c8f0 · outbound

This paper cites • ux(y) = 0 for any y ∈ Ω and x ∈ P with ∥x − y∥ ≥a2ρ(P, Ω).

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift • ux(y) = 0 for any y ∈ Ω and x ∈ P with ∥x − y∥ ≥a2ρ(P, Ω)

Reference 21

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8a5aa1d5-6fac-4459-88c9-de2fe9e499d8 · outbound

This paper cites However, as B increases, the two-stage estimator demonstrates greater accuracy and improved stability, highlighting its necessity under significant covariate shift.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift However, as B increases, the two-stage estimator demonstrates greater accuracy and improved stability, highlighting its necessity under significant covariate shift

Reference 22

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8766d500-bd09-4ee0-858c-c1c4431866f0 · outbound

This paper cites Analysis of Kernel Mean Matching under Covariate Shift.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift Analysis of Kernel Mean Matching under Covariate Shift

Reference 2004

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Observation ad9bd3ba-f069-41ad-8162-11f2c7c6c251 · outbound

This paper cites Let Hf,q n denote the class of all the estimators using S = {(xi, yi = f (xi))}n i=1 to estimate the q-th moment of f under P∗.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift Let Hf,q n denote the class of all the estimators using S = {(xi, yi = f (xi))}n i=1 to estimate the q-th moment of f under P∗

Reference 2012

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f06fe8ee-5e32-44e9-89e8-19fda4edf8fb · outbound

This paper cites The covering radius of randomly distributed points on a manifold.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift The covering radius of randomly distributed points on a manifold

Reference 2017

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 05e66ff0-b56a-4f9d-9f1b-26907c01d088 · outbound

This paper cites Optimal transport for treatment effect estimation.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift Optimal transport for treatment effect estimation

Reference 2019

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f21f7ed2-3786-4a8a-b477-a5285d6342a1 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2021

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source=pdf_text observed=2026-08-06T21:56:37.321987Z digest=sha256:7bd7bc9668d258aff7554997f96eb04d65f40f83535e833b62908952c9b50b66

Observation 37e1c9eb-981d-499c-929a-db208374ba7d · outbound

This paper cites Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation

Reference 2022

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source=pdf_text observed=2026-08-06T21:56:37.430303Z digest=sha256:74022e54c75673a91c39177adaedb8850cd39e3b8cdf9ff7d8e6dc306674266b

Observation ffdfb181-73b3-4e77-ad6b-89882880da54 · outbound

This paper cites Lipschitz density-ratios, structured data, and data-driven tuning.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift Lipschitz density-ratios, structured data, and data-driven tuning

Reference 2023

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:56:37.499291Z digest=sha256:03d87accd88c473cb424fe4812516af3afb0369ff0e3c4b15f4fdc4dc89773d8

Observation 4a39a379-0935-4ff3-84f4-edec64edd661 · outbound

This paper cites Few-Shot Learning via Learning the Representation, Provably.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift Few-Shot Learning via Learning the Representation, Provably

Reference 2024

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Unavailable: canonical work link unavailable.

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