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Paper Citation Record · LEDGER

Bayesian Optimization for Machine Learning : A Practical Guidebook

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1612.04858.

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

pith.paper-citation-record.v1
1612.04858 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T21:36:43.541170Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T15:53:40.860885Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 78000068-fa89-4119-88ed-2ab9788640ad · inbound

Estimating Stellar Atmospheric Parameters and [{\alpha}/Fe] for LAMOST O-M type Stars Using a Spectral Emulator cites this paper.

Estimating Stellar Atmospheric Parameters and [{\alpha}/Fe] for LAMOST O-M type Stars Using a Spectral Emulator Bayesian Optimization for Machine Learning : A Practical Guidebook

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-12T21:36:43.541170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T21:36:43.541170Z digest=sha256:650bc65ec3f8daadf3fc6834ea45fae3ec696f93241816e416749e13ccb0787a

Observation 010e6fe6-02b8-4ff3-9100-fac338c3b119 · inbound

HyperZero: A Customized End-to-End Auto-Tuning System for Recommendation with Hourly Feedback cites this paper.

HyperZero: A Customized End-to-End Auto-Tuning System for Recommendation with Hourly Feedback Bayesian Optimization for Machine Learning : A Practical Guidebook

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-10T00:38:28.726879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T00:38:28.726879Z digest=sha256:83fbfa56325baa7e455c0add7130ce985f64465711325c1ac733489bb8c91a9c

Observation 0e734f59-e122-4250-aafd-a34fe4d2261a · inbound

Sparse minimum Redundancy Maximum Relevance for feature selection cites this paper.

Sparse minimum Redundancy Maximum Relevance for feature selection Bayesian Optimization for Machine Learning : A Practical Guidebook

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T16:12:39.512421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:12:39.512421Z digest=sha256:7ba945a5ae4a75fff5796c54bc80541ec477c92c473feaf1988bbb01d1c2492f

Observation 335ac3e2-a9ea-4785-b6b9-b26b9732f368 · inbound

Exploring the astrophysical origins of binary black holes using normalising flows cites this paper.

Exploring the astrophysical origins of binary black holes using normalising flows Bayesian Optimization for Machine Learning : A Practical Guidebook

Reference 50

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:53:41.024440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T15:53:37.938284Z digest=sha256:6acbfa4b08b1f58d01e04d2896be56a794a467600b6a8adc3acddabbe03951f4