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Paper Citation Record · LEDGER

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals

As of 10 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2607.06750.

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

pith.paper-citation-record.v1
2607.06750 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-10T22:06:56.239466Z

measured 30 of 30 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

30 of 30 outbound references displayed

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External citation measurements

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Outbound references

Observation 286e1b06-e15a-4ab0-ae3e-ad3a9945866e · outbound

This paper cites Improved bounds for universal one-bit compressive sensing.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Improved bounds for universal one-bit compressive sensing

Reference 1

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 1f2b5e8a-1168-448c-8847-71117e4f5691 · outbound

This paper cites Milman.Asymptotic Geometric Analysis, Part I, volume 202 ofMathematical Surveys and Monographs.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Milman.Asymptotic Geometric Analysis, Part I, volume 202 ofMathematical Surveys and Monographs

Reference 2

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 6324281a-1d1f-477c-8b0d-ed0036373df4 · outbound

This paper cites Learning and 1-bit compressed sensing under asymmetric noise.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Learning and 1-bit compressed sensing under asymmetric noise

Reference 3

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ca4d547f-d15c-4548-a0f3-063815b8c445 · outbound

This paper cites 1-bit compressive sensing.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals 1-bit compressive sensing

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:a336b04a0e02fe826b30faca0027e1dbf4866706bd89082f301656096cd4e27d

Observation 31e0eee2-0f81-47f0-b135-7369148ae3de · outbound

This paper cites Robust instance optimal phase-only com- pressed sensing.Information and Inference: A Journal of the IMA, 15(2):iaag014, 06 2026.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Robust instance optimal phase-only com- pressed sensing.Information and Inference: A Journal of the IMA, 15(2):iaag014, 06 2026

Reference 5

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verified fuzzy
raw_fallback, observed 2026-07-10T22:07:39.243697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:87be4c978eaf1c6557bfcf4fba9a392371bde8a5ed63212393454ef135a088f9

Observation 9951afda-19f1-4bca-8d92-b5a94172f77d · outbound

This paper cites Optimal Quantized Compressed Sensing via Projected Gradient Descent.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Optimal Quantized Compressed Sensing via Projected Gradient Descent

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-07-10T22:07:37.099138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:fc0b407810e78644f7176bed65686b4c000c19da6067b54783a659ecc900e3f0

Observation ccfd47db-c742-414b-8202-c4504d2f14a0 · outbound

This paper cites One-bit phase retrieval: Optimal rates and efficient algorithms.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals One-bit phase retrieval: Optimal rates and efficient algorithms

Reference 7

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verified fuzzy
raw_fallback, observed 2026-07-10T22:07:38.779478Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:1a15d54dcbad341ab58faaee8c4023314cb9d76dba3f7dae0bf3e2285a9ef268

Observation 1add7a85-f7c8-4f02-a6ab-ddfbdceaaa1b · outbound

This paper cites Adaboost and robust one-bit compressed sensing.Mathematical Statistics and Learning, 5(1):117–158, 2022.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Adaboost and robust one-bit compressed sensing.Mathematical Statistics and Learning, 5(1):117–158, 2022

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:f0b905384ac70dd4e85efec31e7abc861b103c42c88e9a9931f69d3aa4437c6a

Observation d0d98a22-f36b-4fc9-92f0-6e28200a8501 · outbound

This paper cites One-bit compressed sensing with partial gaussian circulant matrices.Information and Inference: A Journal of the IMA, 9(3):601– 626, 2020.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals One-bit compressed sensing with partial gaussian circulant matrices.Information and Inference: A Journal of the IMA, 9(3):601– 626, 2020

Reference 9

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verified fuzzy
raw_fallback, observed 2026-07-10T22:07:39.267307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:e2c58f92902d76766fb7052021f5f2eb6f7d9daa82440e90f730d360dc91808c

Observation ddb6b41b-532e-4eff-9d7d-be7c1c964099 · outbound

This paper cites Non-gaussian hyperplane tessellations and robust one-bit compressed sensing.Journal of the European Mathematical Society, 23(9):2913–2947, 2021.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Non-gaussian hyperplane tessellations and robust one-bit compressed sensing.Journal of the European Mathematical Society, 23(9):2913–2947, 2021

Reference 10

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:c329f6e1e0861b2560d7e503662973ae41d005805a4f31e077e796dd8bf15d31

Observation 5dccd558-fc0a-4ff9-9a81-0b8b1f7df2df · outbound

This paper cites Robust one-bit compressed sensing with partial circulant matrices.The Annals of Applied Probability, 33(3):1874–1903, 2023.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Robust one-bit compressed sensing with partial circulant matrices.The Annals of Applied Probability, 33(3):1874–1903, 2023

Reference 11

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:ddaa04da605301304a887139019a5b8fa7720bf0c23da33f0103738831f4a3ab

Observation 6e6fe5df-75a9-4125-9331-6cf5daad9047 · outbound

This paper cites Sharp estimates on random hyperplane tessellations.SIAM Journal on Mathematics of Data Science, 4(4):1396–1419, 2022.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Sharp estimates on random hyperplane tessellations.SIAM Journal on Mathematics of Data Science, 4(4):1396–1419, 2022

Reference 12

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:46c2e2b6c84647f5a9da695461e5c7c700c44500266e472f3dd802b836f06299

Observation 07be3377-ea21-46b0-8056-13f620aba56f · outbound

This paper cites A resolution of the gaussian hyperplane tessellation conjecture on the sphere.Applied and Computational Harmonic Analysis, page 101903, 2026.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals A resolution of the gaussian hyperplane tessellation conjecture on the sphere.Applied and Computational Harmonic Analysis, page 101903, 2026

Reference 13

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:27024f0b6d6bd72be80f10e43ea0169f1e44aa56b8c10076293e6ab944ddb0b7

Observation b8ab7809-a3e1-4546-bd8b-7c04d54c34ff · outbound

This paper cites Nbiht: An efficient algorithm for 1-bit compressed sensing with optimal error decay rate.IEEE Transactions on Information Theory, 68(2):1157–1177, 2021.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Nbiht: An efficient algorithm for 1-bit compressed sensing with optimal error decay rate.IEEE Transactions on Information Theory, 68(2):1157–1177, 2021

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:38be22d40a556c0db537e1a91c3c98c87494b4ca17725787fda6b57633c872ff

Observation 9d2de407-141d-40a3-a7c5-a31d40a14f82 · outbound

This paper cites On the sample complexity of parameter estimation in logistic regression with normal design.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals On the sample complexity of parameter estimation in logistic regression with normal design

Reference 15

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verified fuzzy
raw_fallback, observed 2026-07-10T22:07:39.100669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:10e5d36b32972d2315542d76bb5325e4592463466bc3522ca38a65646423286b

Observation 3a17f1b0-b1fe-4ba8-9386-f5ec9d242660 · outbound

This paper cites Robust 1- bit compressive sensing via binary stable embeddings of sparse vectors.IEEE Transactions on Information Theory, 59(4):2082–2102, 2013.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Robust 1- bit compressive sensing via binary stable embeddings of sparse vectors.IEEE Transactions on Information Theory, 59(4):2082–2102, 2013

Reference 16

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verified fuzzy
raw_fallback, observed 2026-07-10T22:07:39.040665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:416f057df26290631df752e6b6a58fb1a981607fd871d0a8c5dd55aea6cdc559

Observation 68307ee1-a72a-48d2-9dbe-948c4a1dd822 · outbound

This paper cites Quantized com- pressed sensing by rectified linear units.IEEE Transactions on Information Theory, 67(6):4125– 4149, 2021.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Quantized com- pressed sensing by rectified linear units.IEEE Transactions on Information Theory, 67(6):4125– 4149, 2021

Reference 17

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raw_fallback, observed 2026-07-10T22:07:39.060829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:280ef414bba5c498005ebd4634fd4f652684a97625f9c63499632176682ac524

Observation daf2ced6-caa0-404f-bdf3-a3c8ae2c11c3 · outbound

This paper cites Efficient learning of gener- alized linear and single index models with isotonic regression.Advances in Neural Information Processing Systems, 24, 2011.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Efficient learning of gener- alized linear and single index models with isotonic regression.Advances in Neural Information Processing Systems, 24, 2011

Reference 18

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verified fuzzy
raw_fallback, observed 2026-07-10T22:07:39.318089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:82052d25af2c08854799618a4d64cc6d0000140b7403e2c33227d8cbf63cb7e9

Observation 817e1c2c-7878-4148-9f33-7ffd1f0f9e3c · outbound

This paper cites One-bit compressive sensing with norm estima- tion.IEEE Transactions on Information Theory, 62(5):2748–2758, 2016.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals One-bit compressive sensing with norm estima- tion.IEEE Transactions on Information Theory, 62(5):2748–2758, 2016

Reference 19

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verified fuzzy
raw_fallback, observed 2026-07-10T22:07:38.994578Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 227f45f6-a460-4c15-be9e-db2f5a33a2ed · outbound

This paper cites an unresolved cited work.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Unresolved cited work

Reference 20

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unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:0a55898a5b1944cdcee6bdea4558a35ecf44653d162cbad70b3e85f45c5a9430

Observation 59cb065d-25f3-4c25-a5ae-85ef5c27f351 · outbound

This paper cites On the sample complexity of pac learning half-spaces against the uniform distribution.IEEE Transactions on Neural Networks, 6(6):1556–1559, 1995.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals On the sample complexity of pac learning half-spaces against the uniform distribution.IEEE Transactions on Neural Networks, 6(6):1556–1559, 1995

Reference 21

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verified fuzzy
raw_fallback, observed 2026-07-10T22:07:39.060066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:98bb330dd6d0ac4ebad09223ca0540544034e4b1d7533975f8465500e8e5fd0e

Observation 7cef824c-7dcb-4385-9a40-4bfd617d3b88 · outbound

This paper cites Binary iterative hard thresholding converges with optimal number of measurements for 1-bit compressed sensing.Journal of the ACM, 71(5):1–64, 2024.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Binary iterative hard thresholding converges with optimal number of measurements for 1-bit compressed sensing.Journal of the ACM, 71(5):1–64, 2024

Reference 22

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verified fuzzy
raw_fallback, observed 2026-07-10T22:07:39.216305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:46aaa84a04db9e7b73ba8a5c6dc7d13ab1d9a39a58bd3e829d1974d90051b176

Observation d54e8647-d3d7-4bad-8707-ed2006656d59 · outbound

This paper cites Robust 1-bit compressed sensing with iterative hard thresholding.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Robust 1-bit compressed sensing with iterative hard thresholding

Reference 23

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verified fuzzy
raw_fallback, observed 2026-07-10T22:07:38.939994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:dbd63202dfebd009ce87933de99920f9ef6c1c2b804bae90990779e74af17474

Observation f88bd443-9535-40fc-8586-3a295ca73b34 · outbound

This paper cites Near-Optimal Bounds for Binary Embeddings of Arbitrary Sets.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Near-Optimal Bounds for Binary Embeddings of Arbitrary Sets

Reference 24

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verified exact
local_arxiv, observed 2026-07-10T22:07:37.070313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:81045edfafdbcaeec7708aea1e5180839dec181e201709ac3e3953105330a055

Observation 009dd5cc-8d6c-4c46-a82c-43d8f20108a3 · outbound

This paper cites Robust 1-bit compressed sensing and sparse logistic regres- sion: A convex programming approach.IEEE Transactions on Information Theory, 59(1):482– 494, 2012.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Robust 1-bit compressed sensing and sparse logistic regres- sion: A convex programming approach.IEEE Transactions on Information Theory, 59(1):482– 494, 2012

Reference 25

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raw_fallback, observed 2026-07-10T22:07:38.940271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:a1e0c267e55307ffae0fcdbdd7698f97f379f204910586159742b5ed23097d22

Observation d96f045c-7793-4101-beec-d4f638c78d17 · outbound

This paper cites One-bit compressed sensing by linear programming.Com- munications on Pure and Applied Mathematics, 66(8):1275–1297, 2013.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals One-bit compressed sensing by linear programming.Com- munications on Pure and Applied Mathematics, 66(8):1275–1297, 2013

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raw_fallback, observed 2026-07-10T22:07:39.267023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:715e8d9af75988726b885ac27cf34dfaf4a80da106b09ac4ed8685ff31d00051

Observation 1cc073b9-f18d-4139-9153-8676d55669a3 · outbound

This paper cites Dimension reduction by random hyperplane tessellations.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Dimension reduction by random hyperplane tessellations

Reference 27

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verified fuzzy
raw_fallback, observed 2026-07-10T22:07:38.840816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:9b65ff88ef6383f705aab41fba04d328a7e292fe3900f797c18e1d8badfccebd

Observation 866f6435-364a-4edb-a87c-ad276c87fdf0 · outbound

This paper cites The generalized lasso for sub-gaussian measure- ments with dithered quantization.IEEE Transactions on Information Theory, 66(4):2487–2500, 2020.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals The generalized lasso for sub-gaussian measure- ments with dithered quantization.IEEE Transactions on Information Theory, 66(4):2487–2500, 2020

Reference 28

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raw_fallback, observed 2026-07-10T22:07:39.211929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:57fe70d7b615cae4bed4bda92bc234ac70447788c3bccec0cb0f1e1969fb212b

Observation b3e25aaa-3638-4904-b15b-b153b7138203 · outbound

This paper cites Quantized compressive sensing with rip matrices: The benefit of dithering.Information and Inference: A Journal of the IMA, 9(3):543–586, 2020.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Quantized compressive sensing with rip matrices: The benefit of dithering.Information and Inference: A Journal of the IMA, 9(3):543–586, 2020

Reference 29

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verified fuzzy
raw_fallback, observed 2026-07-10T22:07:38.818218Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:249c8a7f12ea89576a2e5a3579e4c9c789aaaeb698fe830e3ab9f3f1a34f9dd5

Observation 02af0c46-d0d0-4549-b333-c8e317005692 · outbound

This paper cites Now notice that the condition (58) is equivalent tos1− q 2 rq ≤k 1− q 2 .Hence∥u∥ q ≤k 1 q − 1 2, meaning thatu∈k 1 q − 1 2 Bn q by viewinguas(u ⊤,0 n−s)⊤.

Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals Now notice that the condition (58) is equivalent tos1− q 2 rq ≤k 1− q 2 .Hence∥u∥ q ≤k 1 q − 1 2, meaning thatu∈k 1 q − 1 2 Bn q by viewinguas(u ⊤,0 n−s)⊤

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T22:07:39.295848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T22:06:56.239466Z digest=sha256:cf226109eb7216eabc2987a9dc38ec881d9a644b349eca69fa5e4dc735c0d81b

Pith citing papers

No inbound Pith citation observations are available.