Paper Citation Record · LEDGER

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random

As of 14 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2501.09851.

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

pith.paper-citation-record.v1
2501.09851 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:51:48.378707Z

measured 52 of 52 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 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

52 of 52 outbound references displayed

verified exact3
verified fuzzy41
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f90e00ea-75d1-4392-ae29-78812567fd54 · outbound

This paper cites Efficient learning of linear separators under bounded noise.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Efficient learning of linear separators under bounded noise

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.378045Z

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 8976cfe4-7689-4af2-a599-08db56895827 · outbound

This paper cites Angluin and P.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Angluin and P

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.364328Z

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 7a79ee63-7070-4fa1-bb14-bcd9efcb26c6 · outbound

This paper cites Arriaga and S.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Arriaga and S

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.349434Z

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 e4e1d164-de98-4840-9bda-dcee1a549bef · outbound

This paper cites Frieze, Ravi Kannan, and Santosh S.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Frieze, Ravi Kannan, and Santosh S

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.334858Z

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 49180c4a-f2c3-4e01-8c63-7d60f5fe484a · outbound

This paper cites Dueling optimization with a monotone adversary.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Dueling optimization with a monotone adversary

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.319373Z

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 3088c329-bfd1-4ab4-8ec6-ba7bc0dd9a61 · outbound

This paper cites an unresolved cited work.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-10T19:51:49.303683Z

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 e1a7dee0-4594-4297-812b-841f00c2d128 · outbound

This paper cites Coloring random and semi-random k-colorable graphs.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Coloring random and semi-random k-colorable graphs

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.288140Z

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 56f8474c-a0b3-41c6-a019-45f5fc287a72 · outbound

This paper cites Learning linear threshold functions in the presence of classification noise.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Learning linear threshold functions in the presence of classification noise

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.272741Z

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 64945dcf-7741-4e21-9d06-423f05718839 · outbound

This paper cites Bylander.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Bylander

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.257304Z

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 542cf8ad-4da0-4a80-a01b-adc77b7391aa · outbound

This paper cites Non-convex matrix completion against a semi-random adversary.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Non-convex matrix completion against a semi-random adversary

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.241615Z

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 122ca958-17cb-45f3-87b1-266a458d5b37 · outbound

This paper cites Classification under misspecification: Halfspaces, generalized linear models, and evolvability.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Classification under misspecification: Halfspaces, generalized linear models, and evolvability

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.225729Z

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 3bf88a2b-1bce-494d-8c87-c7908754f3b5 · outbound

This paper cites an unresolved cited work.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-10T19:51:49.210509Z

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 ecd59605-0975-402f-a374-c73a5dd0076b · outbound

This paper cites Learning noisy perceptrons by a perceptron in polynomial time.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Learning noisy perceptrons by a perceptron in polynomial time

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.195204Z

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 a500e707-8d2d-4210-b22c-0fea7ebcea41 · outbound

This paper cites Complexity theoretic limitations on learning halfspaces.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Complexity theoretic limitations on learning halfspaces

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.180933Z

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 b4e622e4-0b71-4a50-bd2f-bdfac3539352 · outbound

This paper cites Kane, Puqian Wang, and Nikos Zarifis.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Kane, Puqian Wang, and Nikos Zarifis

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.166892Z

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 f69cfe5c-b205-44d5-a495-5152865a7013 · outbound

This paper cites Distribution-independent PAC learning of halfspaces with massart noise.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Distribution-independent PAC learning of halfspaces with massart noise

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.151524Z

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 3a8caa52-dc83-472f-aee5-c105567eed60 · outbound

This paper cites Near-Optimal Statistical Query Hardness of Learning Halfspaces with Massart Noise.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Near-Optimal Statistical Query Hardness of Learning Halfspaces with Massart Noise

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-10T19:51:48.490288Z

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 0860a7d5-f18b-40ce-aef2-c8917c00e483 · outbound

This paper cites Diakonikolas, D.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Diakonikolas, D

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.135145Z

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 d77f6c9f-3d19-4106-bd09-06f41399183a · outbound

This paper cites Learning general halfspaces with general massart noise under the gaussian distribution.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Learning general halfspaces with general massart noise under the gaussian distribution

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.119218Z

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 b774921b-2679-4827-a6c8-cdae9f3499fa · outbound

This paper cites Nearly tight bounds for robust proper learning of halfspaces with a margin.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Nearly tight bounds for robust proper learning of halfspaces with a margin

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.102654Z

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 b00648d2-deb4-4a10-88fe-9a939d7804df · outbound

This paper cites Diakonikolas, D.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Diakonikolas, D

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.085065Z

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 54f84f33-128a-43fa-b00e-22d6a4c5a51e · outbound

This paper cites Forster decomposition and learning halfspaces with noise.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Forster decomposition and learning halfspaces with noise

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.068424Z

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 f52d16ab-f5be-4613-a8ec-40d8105b31cf · outbound

This paper cites Diakonikolas, V.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Diakonikolas, V

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.051732Z

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 cf9d35d5-9714-4cb4-bf8f-fc2d74fbe77c · outbound

This paper cites Diakonikolas, V.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Diakonikolas, V

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.035726Z

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 3a6ded1b-9549-4249-ad5c-93246a883e60 · outbound

This paper cites Diakonikolas, V.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Diakonikolas, V

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:49.019225Z

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 221d77aa-829b-45af-95b3-ccaa43756568 · outbound

This paper cites Learning general halfspaces with adversarial label noise via online gradient descent.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Learning general halfspaces with adversarial label noise via online gradient descent

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T19:51:48.260218Z

Source-reported events for the cited work

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Observation 16538e74-3f1a-4879-b594-e03a1b991996 · outbound

This paper cites Online Learning of Halfspaces with Massart Noise.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Online Learning of Halfspaces with Massart Noise

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T19:51:48.264967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82fb2849-563a-401e-924e-04c8bbefc531 · outbound

This paper cites A near-optimal algorithm for learning margin halfspaces with massart noise.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random A near-optimal algorithm for learning margin halfspaces with massart noise

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.986245Z

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 3ebb525e-2d45-4c3f-9ee4-5e5e226f1c5c · outbound

This paper cites Feldman, P.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Feldman, P

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.968138Z

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 31b706af-4188-4371-9e8c-f0a7cd9039b1 · outbound

This paper cites Robust matrix sensing in the semi-random model.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Robust matrix sensing in the semi-random model

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.952986Z

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 8dfeb719-2b51-4d22-8a72-a1c6cf6737a9 · outbound

This paper cites Agnostically Learning Single-Index Models using Omnipredictors.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Agnostically Learning Single-Index Models using Omnipredictors

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-10T19:51:48.450048Z

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 9412e88b-d20c-45aa-aa48-71eec13d9876 · outbound

This paper cites Hardness of learning halfspaces with noise.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Hardness of learning halfspaces with noise

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.937065Z

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 4a3857e4-804e-40f8-b85c-37c4d360ba8b · outbound

This paper cites Decision theoretic generalizations of the PAC model for neural net and other learning applications.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Decision theoretic generalizations of the PAC model for neural net and other learning applications

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.922229Z

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 d5135c15-8ccd-4d98-b259-961d5292d942 · outbound

This paper cites Hopkins, D.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Hopkins, D

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.783842Z

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 967d04b3-b259-40c2-ba4e-303402af8add · outbound

This paper cites Structured semidefinite programming for recovering structured preconditioners.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Structured semidefinite programming for recovering structured preconditioners

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.766814Z

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 39070a32-b001-4208-98cf-ff8632de6063 · outbound

This paper cites an unresolved cited work.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-10T19:51:48.748881Z

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 2be4ef52-60b6-4d8b-a016-d54df54a3e8d · outbound

This paper cites Slam: Student-label mixing for distillation with unlabeled examples.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Slam: Student-label mixing for distillation with unlabeled examples

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.731917Z

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 a6a06cc2-ca48-46bb-9b22-466756072a69 · outbound

This paper cites Kalai, A.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Kalai, A

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.716161Z

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 26ac2c07-bf53-49ee-9024-169e4e279282 · outbound

This paper cites Kelner, Jerry Li, Allen Liu, Aaron Sidford, and Kevin Tian.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Kelner, Jerry Li, Allen Liu, Aaron Sidford, and Kevin Tian

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.700248Z

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 c4ab2811-27ee-485a-9a6b-2b01176ec6db · outbound

This paper cites Klivans, R.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Klivans, R

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.683448Z

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 b64f0e4c-d767-4659-91a3-62305af7185f · outbound

This paper cites an unresolved cited work.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-08-10T19:51:48.668071Z

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 5b6a4e1c-ca07-407f-9692-57545f4a56df · outbound

This paper cites Kearns, Robert E.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Kearns, Robert E

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.652384Z

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 8f7dc7a8-c54e-45f5-96f6-fafbe76fe35b · outbound

This paper cites Long and R.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Long and R

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.637138Z

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 b8375a02-5403-43c7-91a0-f77f04083ae0 · outbound

This paper cites Massart and E.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Massart and E

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.622310Z

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 12de3ea0-fda5-4a28-926f-ce815dc4e7cc · outbound

This paper cites Nasser and S.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Nasser and S

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.606271Z

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 8204c3a4-8e27-4202-a6be-f7c9b716c22a · outbound

This paper cites Rosenblatt.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Rosenblatt

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.589690Z

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 cea3dde7-e5ea-4db2-8c98-b4556903bf94 · outbound

This paper cites an unresolved cited work.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-10T19:51:48.572149Z

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 b17b67b5-f2ba-4b79-961d-817a75df95f7 · outbound

This paper cites Shalev Shwartz, O.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Shalev Shwartz, O

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.555887Z

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 c33a4e11-5dab-4520-b17d-0c832e0db68c · outbound

This paper cites an unresolved cited work.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-08-10T19:51:48.539384Z

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 5a683adb-4d09-4d21-a12d-5df35629e8df · outbound

This paper cites Improved algorithms for efficient active learning halfspaces with massart and tsybakov noise.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Improved algorithms for efficient active learning halfspaces with massart and tsybakov noise

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.522357Z

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 5f81eba8-3bed-4b2b-b48b-5c45da590d7d · outbound

This paper cites Zhang, P.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Zhang, P

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:48.506181Z

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 5e8c1687-8144-43e2-8e78-b6a237bde182 · outbound

This paper cites Robustly Learning Single-Index Models via Alignment Sharpness.

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Robustly Learning Single-Index Models via Alignment Sharpness

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-08-10T19:51:48.425689Z

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