Paper Citation Record · LEDGER

Cost-aware Stopping for Bayesian Optimization

As of 13 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 2 inbound Pith citation observations for arXiv:2507.12453.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2507.12453 v5

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:56:51.001148Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T14:57:00.263317Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-22T07:24:43.168275Z

Reference resolution

18 of 18 outbound references displayed

verified exact1
verified fuzzy8
unresolved6
parse uncertain0
malformed identifier3
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3223d053-d56b-4282-a38a-180d096a0faa · outbound

This paper cites τX t=2 αEI t−1(xt) # =E.

Cost-aware Stopping for Bayesian Optimization τX t=2 αEI t−1(xt) # =E

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:53.186048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a41562a6-54ef-45f9-b427-e0c30b03af3a · outbound

This paper cites Cost functions: Bayesian regret.In Bayesian regret experiments, we consider three types of evaluation costs: uniform, linear, and periodic.

Cost-aware Stopping for Bayesian Optimization Cost functions: Bayesian regret.In Bayesian regret experiments, we consider three types of evaluation costs: uniform, linear, and periodic

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:52.456563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5990ebf3-8543-47a2-a7a9-de7bd3312b74 · outbound

This paper cites τX t=1 c(xt) # ≤U+C.(19) By Markov’s inequality, for anyδ∈(0,1), Pr.

Cost-aware Stopping for Bayesian Optimization τX t=1 c(xt) # ≤U+C.(19) By Markov’s inequality, for anyδ∈(0,1), Pr

Reference 9

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T16:56:53.012840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a28a3126-2253-4aea-9d71-20ae36bb54f7 · outbound

This paper cites For Bayesian regret experiments, we follow the standard practice to generate the initial random samples using a quasirandom Sobol sequence.

Cost-aware Stopping for Bayesian Optimization For Bayesian regret experiments, we follow the standard practice to generate the initial random samples using a quasirandom Sobol sequence

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:52.829154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c4c2864e-f08e-4df1-b194-27bae28454aa · outbound

This paper cites We also adopt their choice ofδ= 10 −1 and a scale-down factor of5.

Cost-aware Stopping for Bayesian Optimization We also adopt their choice ofδ= 10 −1 and a scale-down factor of5

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:52.632235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ef5f36c3-3279-4192-b368-eaf4fd0f7aaf · outbound

This paper cites On LCBench datasets, some regret-based stopping rules such as SRGap-med and UCB–LCB also frequently exceed the cap.

Cost-aware Stopping for Bayesian Optimization On LCBench datasets, some regret-based stopping rules such as SRGap-med and UCB–LCB also frequently exceed the cap

Reference 15

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T16:56:51.868256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 02f77ebf-ce1b-4bcd-8f55-d5b807fab5bd · outbound

This paper cites underperforming.

Cost-aware Stopping for Bayesian Optimization underperforming

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:51.507128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e666e88d-e92e-466e-8807-7c0b95fb87e0 · outbound

This paper cites an unresolved cited work.

Cost-aware Stopping for Bayesian Optimization Unresolved cited work

Reference 35

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T16:56:51.366311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation afa532de-9fb9-46d3-87bb-c04808ad490d · outbound

This paper cites Results are identical across acquisition functions.

Cost-aware Stopping for Bayesian Optimization Results are identical across acquisition functions

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:51.682353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 79b6bd8f-4c59-4bd9-9b8b-61762ae03f32 · outbound

This paper cites Each subplot shows a scatter plot of actual runtime ( y-axis) against number of model parameters ( x-axis), along with a fitted linear regression line.

Cost-aware Stopping for Bayesian Optimization Each subplot shows a scatter plot of actual runtime ( y-axis) against number of model parameters ( x-axis), along with a fitted linear regression line

Reference 784

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:52.284810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b3ae5c37-6fe5-4132-be4c-72ca9c0b7ee2 · outbound

This paper cites Specifically, they are precomputed and stored for each architecture.

Cost-aware Stopping for Bayesian Optimization Specifically, they are precomputed and stored for each architecture

Reference 1000

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:52.057501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ce17291c-30a1-401e-8664-080a4c4cfa90 · outbound

This paper cites Stopping criteria for boosting automatic experimental design using real-time fMRI with Bayesian optimization.

Cost-aware Stopping for Bayesian Optimization Stopping criteria for boosting automatic experimental design using real-time fMRI with Bayesian optimization

Reference 1997

Resolution: unresolved; no resolver link, observed 2026-08-06T16:56:49.935619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36a703ac-d384-44f8-a73f-28f6dadd0e0c · outbound

This paper cites Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design.

Cost-aware Stopping for Bayesian Optimization Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 2012

Resolution: unresolved; no resolver link, observed 2026-08-06T16:56:50.000771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a88d453-1559-44ba-a271-14fbf68fd004 · outbound

This paper cites Cost-aware Bayesian Optimization.

Cost-aware Stopping for Bayesian Optimization Cost-aware Bayesian Optimization

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-06T16:56:49.870721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 658cc5d6-63bd-4dc0-bc67-ad6b013ee18e · outbound

This paper cites Multi-Step Bayesian Optimization for One-Dimensional Feasibility Determination.

Cost-aware Stopping for Bayesian Optimization Multi-Step Bayesian Optimization for One-Dimensional Feasibility Determination

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T16:56:49.602306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3b945a9-0a4e-468a-8a1a-d9dc72ec44b8 · outbound

This paper cites Constrained multi-fidelity Bayesian optimization with automatic stop condition.

Cost-aware Stopping for Bayesian Optimization Constrained multi-fidelity Bayesian optimization with automatic stop condition

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T16:56:49.668610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8e6389a-2aad-4329-a070-503ab1565d5e · outbound

This paper cites Descending Price Optimally Coordinates Search.

Cost-aware Stopping for Bayesian Optimization Descending Price Optimally Coordinates Search

Reference 2023

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:56:51.183098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7cd8c137-9862-42f2-a334-4d42a956eb8f · outbound

This paper cites Constrained multi-fidelity Bayesian optimization with automatic stop condition.

Cost-aware Stopping for Bayesian Optimization Constrained multi-fidelity Bayesian optimization with automatic stop condition

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T16:56:49.707143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation af3c481f-4303-4b94-b6dc-0ec58f142d7a · inbound

T-TAMER: Provably Taming Trade-offs in ML Serving cites this paper.

T-TAMER: Provably Taming Trade-offs in ML Serving Cost-aware Stopping for Bayesian Optimization

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-04T14:57:00.263317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2747f98-a765-47ea-90d5-85eb3a8bb26b · inbound

Regret-Based $(\epsilon,\delta)$-optimal Stopping Criteria for Bayesian Optimization cites this paper.

Regret-Based $(\epsilon,\delta)$-optimal Stopping Criteria for Bayesian Optimization Cost-aware Stopping for Bayesian Optimization

Reference 30

Resolution: malformed identifier; arxiv_id, observed 2026-06-01T02:02:16.580919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.