Paper Citation Record · LEDGER

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations

As of 12 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 3 inbound Pith citation observations for arXiv:2605.22275.

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

pith.paper-citation-record.v1
2605.22275 v2

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T13:34:56.764763Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T11:15:26.744292Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T23:09:00.798918Z

Reference resolution

23 of 23 outbound references displayed

verified exact0
verified fuzzy0
unresolved23
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ee49c86b-22d6-49a9-ab1d-e3542256d572 · outbound

This paper cites Kernel methods in machine learning,.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Kernel methods in machine learning,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:54.267434Z

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Observation 905edb6b-3325-4a3c-a4a7-ad044d2e7d2b · outbound

This paper cites Supervised learning with quantum- enhanced feature spaces,.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Supervised learning with quantum- enhanced feature spaces,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:54.452922Z

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Observation 4512c4d8-3446-4d48-8fb1-ebdfc695f5f9 · outbound

This paper cites Quantum machine learning in feature hilbert spaces,.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Quantum machine learning in feature hilbert spaces,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:54.540740Z

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Unavailable: canonical work link unavailable.

Observation 961b6386-6154-4262-882d-e1e45d690854 · outbound

This paper cites Barren plateaus in quantum neural network training landscapes,.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Barren plateaus in quantum neural network training landscapes,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:54.629997Z

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Observation 81ce7520-517c-484f-b8aa-5e091cf7c6d2 · outbound

This paper cites Exponential concentration in quantum kernel methods,.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Exponential concentration in quantum kernel methods,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:54.729936Z

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Observation 3b4ac0ce-4a48-40d1-9f45-dc76bd3a2dc5 · outbound

This paper cites In Search of Quantum Advantage: Estimating the Number of Shots in Quantum Kernel Methods.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations In Search of Quantum Advantage: Estimating the Number of Shots in Quantum Kernel Methods

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:54.876648Z

Source-reported events for the cited work

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Observation 279a86f9-5234-4e90-b24b-53093d5f8ac5 · outbound

This paper cites The complexity of quantum support vector machines,.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations The complexity of quantum support vector machines,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:55.007311Z

Source-reported events for the cited work

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Observation 68e4f004-6477-475f-8bd3-1334694b1d25 · outbound

This paper cites Quantum-Efficient Kernel Target Alignment.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Quantum-Efficient Kernel Target Alignment

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:55.061916Z

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Unavailable: canonical work link unavailable.

Observation 5024583b-b956-452c-b45b-1c98002f9e91 · outbound

This paper cites Kernel Matrix Completion for Offline Quantum-Enhanced Machine Learning.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Kernel Matrix Completion for Offline Quantum-Enhanced Machine Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:55.172227Z

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Observation 35e1f3bc-7286-4893-83b5-d3f5a5d52713 · outbound

This paper cites Shot-frugal and Robust quantum kernel classifiers.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Shot-frugal and Robust quantum kernel classifiers

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:55.284744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f08108c-ae2e-4209-bfd2-d75343056a10 · outbound

This paper cites AQKA: Active Quantum Kernel Acquisition Under a Shot Budget.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations AQKA: Active Quantum Kernel Acquisition Under a Shot Budget

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:55.390601Z

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Observation 0d36261e-321c-4a32-97ac-1a28698fdc31 · outbound

This paper cites Optimal algorithmic complexity of inference in quantum kernel methods.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Optimal algorithmic complexity of inference in quantum kernel methods

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:55.465050Z

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Observation f6dffb26-b1cf-49cb-ac5f-1a6c29fd6dce · outbound

This paper cites Quantum computing in the NISQ era and beyond,.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Quantum computing in the NISQ era and beyond,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:55.581175Z

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Observation 25123acf-d035-40ff-abe0-74b73c450726 · outbound

This paper cites Comparative analysis of contem- porary quantum computer processors: Architectures, performance and perspectives,.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Comparative analysis of contem- porary quantum computer processors: Architectures, performance and perspectives,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:55.695439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09daaf96-e13c-4878-87c1-d64a301af225 · outbound

This paper cites Quantum computing with Qiskit.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Quantum computing with Qiskit

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:55.835432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5eaac5d0-1f1f-4f13-9846-2e29f8959af0 · outbound

This paper cites PennyLane: Automatic differentiation of hybrid quantum-classical computations.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations PennyLane: Automatic differentiation of hybrid quantum-classical computations

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:55.993352Z

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Unavailable: canonical work link unavailable.

Observation 30d1b1ea-a7dd-4125-99d5-ba0f34fc0e64 · outbound

This paper cites Libsvm: A library for support vector machines,.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Libsvm: A library for support vector machines,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:56.114613Z

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Observation 65c8417b-367d-42e6-ab38-284a052fc0e6 · outbound

This paper cites Large-Scale Quantum Kernels for Hyperspectral Data Classification.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Large-Scale Quantum Kernels for Hyperspectral Data Classification

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:56.264287Z

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Unavailable: canonical work link unavailable.

Observation c5de5440-fc53-4c92-961c-9e8d1b172bf2 · outbound

This paper cites Provable and scalable quantum Gaussian processes for quantum learning.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Provable and scalable quantum Gaussian processes for quantum learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:56.418751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 265c64f0-5c2f-4244-a5f6-7c23bc853144 · outbound

This paper cites an unresolved cited work.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:56.549955Z

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Observation a5e72a4f-c760-462d-975f-3730f5dcf918 · outbound

This paper cites an unresolved cited work.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Unresolved cited work

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:56.654758Z

Source-reported events for the cited work

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Observation 1e7798c7-c5ff-497e-9b4d-93d9927da226 · outbound

This paper cites Discussion The variance of the kernel estimator decomposes into two contributions: •Asampling (shot) noiseterm, K(1−K) N , which decreases with the number of measurements.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Discussion The variance of the kernel estimator decomposes into two contributions: •Asampling (shot) noiseterm, K(1−K) N , which decreases with the number of measurements

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:56.764763Z

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Observation dee390c9-64af-416b-b602-91c035a75b12 · outbound

This paper cites Available: https://doi.org/10.1214/009053607000000677.

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations Available: https://doi.org/10.1214/009053607000000677

Reference 2008

Resolution: unresolved; no resolver link, observed 2026-08-02T13:34:54.348367Z

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Pith citing papers

Observation e2fe3ad4-64c6-468d-83c4-5d8e04db1833 · inbound

Active Quantum Kernel Acquisition for Gaussian Process Regression cites this paper.

Active Quantum Kernel Acquisition for Gaussian Process Regression Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations

Reference 7

Resolution: metadata mismatch; local_arxiv, observed 2026-06-30T10:24:36.362424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8b239f1c-058a-49e8-a9e1-cbf60e31579b · inbound

Active Quantum Kernel Acquisition for Gaussian Process Regression cites this paper.

Active Quantum Kernel Acquisition for Gaussian Process Regression Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations

Reference 7

Resolution: metadata mismatch; local_arxiv, observed 2026-07-03T23:09:00.800509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7bcce1f9-42bd-49d7-8bcd-ffa21f9f9a93 · inbound

Active Quantum Kernel Acquisition for Gaussian Process Regression cites this paper.

Active Quantum Kernel Acquisition for Gaussian Process Regression Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-12T11:15:26.744292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.