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Paper Citation Record · LEDGER

Learning Juntas under Markov Random Fields

As of 10 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 2 inbound Pith citation observations for arXiv:2506.00764.

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

pith.paper-citation-record.v1
2506.00764 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:10:52.863406Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

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

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:34:16.625479Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T22:30:52.949291Z

Reference resolution

43 of 43 outbound references displayed

  • verified exact2
  • verified fuzzy39
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c14fa93f-5bf7-4189-9bf4-419f89bacd09 · outbound

This paper cites Public-key cryptography from different assumptions.

Learning Juntas under Markov Random Fields Public-key cryptography from different assumptions

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:59.090743Z

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=arxiv_source observed=2026-08-07T12:10:49.726296Z digest=sha256:2b0c02da32f1a50d77e08e2b4c14ce5d3c88284b3e8e7ce88cfa199cec5a3131

Observation 3f811d25-b2b7-4d4f-a5a3-24fdfeb21c86 · outbound

This paper cites Learning factor graphs in polynomial time and sample complexity.

Learning Juntas under Markov Random Fields Learning factor graphs in polynomial time and sample complexity

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:58.855445Z

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=arxiv_source observed=2026-08-07T12:10:49.806707Z digest=sha256:78c5db2ef88d60f70766e7717d28d1003a892f6042427c9206534f1a526d31dc

Observation c59d4cf7-edd3-45b0-825a-fa7ae1c80cac · outbound

This paper cites Agnostically learning juntas from random walks, 2008.

Learning Juntas under Markov Random Fields Agnostically learning juntas from random walks, 2008

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:58.612935Z

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=arxiv_source observed=2026-08-07T12:10:49.943589Z digest=sha256:0505bf9fd4190a57104455325de729edcdb161db02fe16ad5eb49b24fbf509f3

Observation 0d77d2ca-949b-4b42-996a-6463a6d5c9c7 · outbound

This paper cites Id3 learns juntas for smoothed product distributions.

Learning Juntas under Markov Random Fields Id3 learns juntas for smoothed product distributions

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:58.418923Z

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=arxiv_source observed=2026-08-07T12:10:50.026129Z digest=sha256:dff0cd5f727171f335965f5578456bdbcff7f06e2455a1e7fd198a19bf57a176

Observation 8d7b3158-36dd-434f-964e-5da45e7707b4 · outbound

This paper cites Weakly learning dnf and characterizing statistical query learning using fourier analysis.

Learning Juntas under Markov Random Fields Weakly learning dnf and characterizing statistical query learning using fourier analysis

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:58.230993Z

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=arxiv_source observed=2026-08-07T12:10:50.121268Z digest=sha256:d67b81790000557c8470b767d9f37dfb1d73859b36643e27ce992993477da1e5

Observation 42fe576d-9328-457c-be62-72b8215e70ce · outbound

This paper cites Near-optimal learning of tree-structured distributions by chow-liu.

Learning Juntas under Markov Random Fields Near-optimal learning of tree-structured distributions by chow-liu

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:58.082206Z

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=arxiv_source observed=2026-08-07T12:10:50.172105Z digest=sha256:8beea8934e4673a921fd3f09f0659752f5e9469808ac6a7f133aefb47b1b32a1

Observation 2b3c1f07-aba4-46d2-b1e8-b307da4c7274 · outbound

This paper cites Blum and Pat Langley.

Learning Juntas under Markov Random Fields Blum and Pat Langley

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:57.934299Z

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=arxiv_source observed=2026-08-07T12:10:50.275521Z digest=sha256:a2b90f5a4fbb0b083882aaa5b8eaec3a387a7735b50654a720e74d8538912204

Observation 402ae891-f2d6-4ccd-b183-60a6ce2467a7 · outbound

This paper cites Improved bounds for testing juntas.

Learning Juntas under Markov Random Fields Improved bounds for testing juntas

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:57.774626Z

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=arxiv_source observed=2026-08-07T12:10:50.369859Z digest=sha256:961b93c9a74af0a5378efeb6bb0c05ebd7176adac5d5bfcfb0daa6aa5fdad157

Observation bf3f7cbb-5d9a-4bae-b1cd-f0fc924c5a35 · outbound

This paper cites Testing juntas nearly optimally.

Learning Juntas under Markov Random Fields Testing juntas nearly optimally

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:57.581882Z

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=arxiv_source observed=2026-08-07T12:10:50.413762Z digest=sha256:548cbeadca09032dbe43d91883ca597a5906b834ab665838f79479a0507f8ddf

Observation 2aaec35d-56cc-4d85-937c-1e783115c18a · outbound

This paper cites Relevant examples and relevant features: Thoughts from computational learning theory.

Learning Juntas under Markov Random Fields Relevant examples and relevant features: Thoughts from computational learning theory

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:57.401706Z

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=arxiv_source observed=2026-08-07T12:10:50.454489Z digest=sha256:575b40059e5f7c2d532f762f4f9428bae2f58444a59e154c49b1415254ed718a

Observation 51825a21-c69f-4ce6-87aa-511765cd1491 · outbound

This paper cites Bshouty, E.

Learning Juntas under Markov Random Fields Bshouty, E

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:57.239577Z

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=arxiv_source observed=2026-08-07T12:10:50.509187Z digest=sha256:02f91e6e2993f8b8c19fab186b910eeed49cba1d08bd324948b16cc917c3e57b

Observation 84c362e3-8b0b-4780-9a47-0aeee785dc53 · outbound

This paper cites Reconstruction of markov random fields from samples: Some observations and algorithms.

Learning Juntas under Markov Random Fields Reconstruction of markov random fields from samples: Some observations and algorithms

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:57.040463Z

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=arxiv_source observed=2026-08-07T12:10:50.577177Z digest=sha256:681b57409fb249dd7eaaa67ed7fe1500cbf52c0300edf4b0bec07283b5ec8a17

Observation bc35fa2b-8c38-49ab-a33a-22091d2fd26f · outbound

This paper cites Efficiently learning ising models on arbitrary graphs.

Learning Juntas under Markov Random Fields Efficiently learning ising models on arbitrary graphs

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:56.834636Z

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=arxiv_source observed=2026-08-07T12:10:50.663865Z digest=sha256:9f9c94e6b103abcba36ecd7e3b4a8051799dd3e24455eb8b1ec2930d48a1140d

Observation 2ef59dcd-fb50-4567-a4ba-9e34c66b8ef5 · outbound

This paper cites Markov fields on finite graphs and lattices.

Learning Juntas under Markov Random Fields Markov fields on finite graphs and lattices

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:56.690799Z

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=arxiv_source observed=2026-08-07T12:10:50.698020Z digest=sha256:f220dd393a8cdca2330269866844aaa623bd43e6aa7424156f216faf6d5ca5ac

Observation 71248075-528d-421e-81f6-fff3ab25f7c0 · outbound

This paper cites Learning the Sherrington-Kirkpatrick Model Even at Low Temperature.

Learning Juntas under Markov Random Fields Learning the Sherrington-Kirkpatrick Model Even at Low Temperature

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:10:53.185922Z

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=arxiv_source observed=2026-08-07T12:10:50.753145Z digest=sha256:11ecaf6e8b9d65eea1e2a400371f3ba48066bef915b4e1d51822c50c48117981

Observation 4aa23442-262c-4782-83ac-f2922f1e787f · outbound

This paper cites Smoothed analysis for learning concepts with low intrinsic dimension.

Learning Juntas under Markov Random Fields Smoothed analysis for learning concepts with low intrinsic dimension

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:56.546315Z

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=arxiv_source observed=2026-08-07T12:10:50.786241Z digest=sha256:fdec60011d1be50d6c072cf4101b2acb1dfe5074b2aa3cbe1e8505717b1c6a75

Observation dbe93f9c-5596-4643-b622-de7ee1bf23de · outbound

This paper cites Approximating discrete probability distributions with dependence trees.

Learning Juntas under Markov Random Fields Approximating discrete probability distributions with dependence trees

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T12:10:50.805689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:10:50.805689Z digest=sha256:6068ea45925e0a51ead3b98642a0eead3e470c8468b90cd0193a7338b9948d09

Observation 87bacd2a-437f-4eb1-ac8a-397b26d6b4d6 · outbound

This paper cites Learning ising models from one or multiple samples.

Learning Juntas under Markov Random Fields Learning ising models from one or multiple samples

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:56.381990Z

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 459ab760-f150-485e-b93c-04961f851fa4 · outbound

This paper cites Outlier-robust learning of ising models under dobrushin’s condition.

Learning Juntas under Markov Random Fields Outlier-robust learning of ising models under dobrushin’s condition

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:56.317260Z

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=arxiv_source observed=2026-08-07T12:10:50.986211Z digest=sha256:116471f377ba075637ea6dbcb5c432117838fbc9143622e02d15e983e716c4b7

Observation d7a288c9-389f-4e34-897e-669b2a1d8745 · outbound

This paper cites Testing juntas.

Learning Juntas under Markov Random Fields Testing juntas

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:56.243188Z

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=arxiv_source observed=2026-08-07T12:10:51.055243Z digest=sha256:951772bc1040ea83ab4dbd3b1436095022d4502ee140e7662693e31d179a640b

Observation a4dd99df-508e-4e07-8d32-d8cbebfb4ea5 · outbound

This paper cites Learning ising models with independent failures.

Learning Juntas under Markov Random Fields Learning ising models with independent failures

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:56.181511Z

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=arxiv_source observed=2026-08-07T12:10:51.119692Z digest=sha256:50edbb2cf8b3f307fb94547c2e930a2598ac7a3f44c81f072072c8dd45e6e66d

Observation 4bbd9d23-0723-4d62-9bed-0e508dd0d6c3 · outbound

This paper cites Bypassing the Noisy Parity Barrier: Learning Higher-Order Markov Random Fields from Dynamics.

Learning Juntas under Markov Random Fields Bypassing the Noisy Parity Barrier: Learning Higher-Order Markov Random Fields from Dynamics

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:10:53.043047Z

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=arxiv_source observed=2026-08-07T12:10:51.207874Z digest=sha256:80b326c2c822184c20fc5b1091795e64a986ac3eb959ce315be6883d6eec7455

Observation 5e99d183-190a-4c54-9d44-61a15217b316 · outbound

This paper cites Information theoretic properties of markov random fields, and their algorithmic applications.

Learning Juntas under Markov Random Fields Information theoretic properties of markov random fields, and their algorithmic applications

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:56.066577Z

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=arxiv_source observed=2026-08-07T12:10:51.283229Z digest=sha256:f7cfc3670d8f283237e5bde8c25e86ae3b6fa22c1aac62f0d233c53058489a74

Observation b8986740-b813-42ef-b23b-0183dcf9b347 · outbound

This paper cites Smoothed analysis of online and differentially private learning.

Learning Juntas under Markov Random Fields Smoothed analysis of online and differentially private learning

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:55.887797Z

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=arxiv_source observed=2026-08-07T12:10:51.376468Z digest=sha256:2ea349ea5548e3df9ec9864a973e7b83f946941b05f28324cc311a2ff5f3de89

Observation 8cc57d43-a9e5-4c0f-9473-c596b0f773b3 · outbound

This paper cites Smoothed analysis with adaptive adversaries.

Learning Juntas under Markov Random Fields Smoothed analysis with adaptive adversaries

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:55.707768Z

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=arxiv_source observed=2026-08-07T12:10:51.462390Z digest=sha256:f061f8375913e07adbd4d2de01a5f7f364195cb2b51fb7d1ea74685c1db67579

Observation 31ce9f80-1bdb-4949-883e-9980d88bd8f2 · outbound

This paper cites Jackson and Karl Wimmer.

Learning Juntas under Markov Random Fields Jackson and Karl Wimmer

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:55.573067Z

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=arxiv_source observed=2026-08-07T12:10:51.532002Z digest=sha256:153eb000c2b66389787ed5ce8857afdb860fca164dce07fd27d6e54730918cd3

Observation 764d0311-6ef8-4a64-bb99-176cc0bc1112 · outbound

This paper cites Efficient noise-tolerant learning from statistical queries.

Learning Juntas under Markov Random Fields Efficient noise-tolerant learning from statistical queries

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:55.420226Z

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=arxiv_source observed=2026-08-07T12:10:51.609804Z digest=sha256:a01539d5c993e01a9eaf5599b5f8bc3d4aae34dc293fbef46d19da6a9065b2b5

Observation 5142bc12-532b-443d-a911-cbc80a239efd · outbound

This paper cites Mcmc learning.

Learning Juntas under Markov Random Fields Mcmc learning

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:55.310470Z

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=arxiv_source observed=2026-08-07T12:10:51.674141Z digest=sha256:adff060f7742b578d50f9aa225483a159b71ba0be6134e66562bf80f1a7a86a6

Observation a355d7fb-ca25-4376-95e5-f08697360eb3 · outbound

This paper cites Klivans and Raghu Meka.

Learning Juntas under Markov Random Fields Klivans and Raghu Meka

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:55.185388Z

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=arxiv_source observed=2026-08-07T12:10:51.760249Z digest=sha256:f53ad9eedc2a402bae0466b97195d1f63bdbbe1fdb55811b5e9b282ca80e9340

Observation 90c92a97-f0e3-4c44-9576-fad811fb5c1d · outbound

This paper cites Learning and smoothed analysis.

Learning Juntas under Markov Random Fields Learning and smoothed analysis

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:55.076746Z

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=arxiv_source observed=2026-08-07T12:10:51.843278Z digest=sha256:a5bc79e5970b407e9da50ca2a4072ebb3d330ff90671bf9798284237297f3943

Observation e21e68c0-d3d4-42cd-8b98-68abbf8da2d7 · outbound

This paper cites Decision trees are PAC-learnable from most product distributions: a smoothed analysis.

Learning Juntas under Markov Random Fields Decision trees are PAC-learnable from most product distributions: a smoothed analysis

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T12:10:51.930523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:10:51.930523Z digest=sha256:1f9e4155363bc8156a3ce001cd15b0f13aa24ef5bdc6c8a9036510bcab81c328

Observation f7348139-3e71-49ae-8b08-b4bd0ecb57ae · outbound

This paper cites Learning to sample from censored markov random fields.

Learning Juntas under Markov Random Fields Learning to sample from censored markov random fields

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:54.945818Z

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=arxiv_source observed=2026-08-07T12:10:52.024671Z digest=sha256:e20633a48251abec1386a2de1a563e1857e06387623942ce90fb40c918f55ebe

Observation 5d9baaa1-6737-4887-98a3-9d05693a67d9 · outbound

This paper cites Servedio.

Learning Juntas under Markov Random Fields Servedio

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:54.824592Z

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=arxiv_source observed=2026-08-07T12:10:52.136481Z digest=sha256:d5020a1eb38d49c2622099ad9efca800759c78a9088d4f5941da823a7a75fbe9

Observation 67e283b1-4ed3-4d95-8585-a4ef4e50d234 · outbound

This paper cites Greedy learning of markov network structure.

Learning Juntas under Markov Random Fields Greedy learning of markov network structure

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:54.672438Z

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=arxiv_source observed=2026-08-07T12:10:52.235484Z digest=sha256:02549644f6e2711223a8badcf27a69e9d5ca69b475c14e2eca0f24de8237e121

Observation 545bdbbc-4e1d-4763-9764-1076b85d8f1e · outbound

This paper cites Proclaiming dictators and juntas or testing boolean formulae.

Learning Juntas under Markov Random Fields Proclaiming dictators and juntas or testing boolean formulae

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:54.529929Z

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=arxiv_source observed=2026-08-07T12:10:52.312663Z digest=sha256:09c72e98d838ec9e8ff35551b6234d2e93b3b6ecd416436d122f1d2c9cdf91d9

Observation 2bdf4c17-315d-4f9f-807f-fb41e9edc409 · outbound

This paper cites On learning ising models under huber's contamination model.

Learning Juntas under Markov Random Fields On learning ising models under huber's contamination model

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:54.405494Z

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=arxiv_source observed=2026-08-07T12:10:52.386875Z digest=sha256:55c25e52b74955028f82a95193f65c6c6e91865a84f252ef9b1970dc9b418ae2

Observation 8a534746-17fe-4f52-b777-08ed496da169 · outbound

This paper cites Spielman and Shang-Hua Teng.

Learning Juntas under Markov Random Fields Spielman and Shang-Hua Teng

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:54.281878Z

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source=arxiv_source observed=2026-08-07T12:10:52.450664Z digest=sha256:ae1c02932d52003bb9c05b701f42e7509614018dca447f2c8774775b0851a81e

Observation 0b78679e-6d62-4301-88fa-9f1e5ae830ce · outbound

This paper cites Information-theoretic limits of selecting binary graphical models in high dimensions.

Learning Juntas under Markov Random Fields Information-theoretic limits of selecting binary graphical models in high dimensions

Reference 38

Resolution
verified fuzzy
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source=arxiv_source observed=2026-08-07T12:10:52.527746Z digest=sha256:9000d58aa49e1a4311b25ef145e526974be4df05aca0798b5f016c852d979a9d

Observation 59b14a0a-f419-4077-b703-1ef40043e1f9 · outbound

This paper cites Learning graphs with a few hubs.

Learning Juntas under Markov Random Fields Learning graphs with a few hubs

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:53.993524Z

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source=arxiv_source observed=2026-08-07T12:10:52.594425Z digest=sha256:692cbdc3c7d6bc2364fe77f550d7a613347a2deb514ddba4dc2710aac82b7f11

Observation a3a284ab-b75b-4080-861a-65df306635b9 · outbound

This paper cites Finding correlations in subquadratic time, with applications to learning parities and juntas.

Learning Juntas under Markov Random Fields Finding correlations in subquadratic time, with applications to learning parities and juntas

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:53.857477Z

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source=arxiv_source observed=2026-08-07T12:10:52.667891Z digest=sha256:f57f5fb00425b9c685b16053f93459bad17528cbbfab8abd02b089d504549583

Observation a2f62ba8-17be-42f3-9de1-d9cff061e311 · outbound

This paper cites Lokhov, and Michael Chertkov.

Learning Juntas under Markov Random Fields Lokhov, and Michael Chertkov

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:53.686490Z

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source=arxiv_source observed=2026-08-07T12:10:52.700667Z digest=sha256:86f1ffe63e0e8381e5fd02630c0e8b166816477c42dd88d4901bae1c7621c1c0

Observation 4096cb9a-f237-4fb4-b2be-e96e85fdcdbd · outbound

This paper cites High-dimensional graphical model selection using _1 -regularized logistic regression.

Learning Juntas under Markov Random Fields High-dimensional graphical model selection using _1 -regularized logistic regression

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:53.474812Z

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source=arxiv_source observed=2026-08-07T12:10:52.786413Z digest=sha256:b99b11882d156f7727200fd852bc7824062cc0f6159f52b1cbf629cfc3c8ad0a

Observation 60159897-dc12-4051-89d5-0593a5fb1bad · outbound

This paper cites Sparse logistic regression learns all discrete pairwise graphical models.

Learning Juntas under Markov Random Fields Sparse logistic regression learns all discrete pairwise graphical models

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:10:53.338131Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T12:10:52.863406Z digest=sha256:22973ae16e95ac2f3b961c96316c9e62afb3ae95db6893c197972915f1b45ebd

Pith citing papers

Observation f37d323b-f737-477b-b7fb-6fbc2621d801 · inbound

Low-dimensional Functions are Efficiently Learnable under Randomly Biased Distributions cites this paper.

Low-dimensional Functions are Efficiently Learnable under Randomly Biased Distributions Learning Juntas under Markov Random Fields

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-08T15:34:16.625479Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T15:34:16.625479Z digest=sha256:b5b5c93442c4a74354d38507257505dc05b2c5391ca565d330e337a91491bdb2

Observation ce7cc849-353f-489f-b93e-f9b2dd599579 · inbound

Learning $\mathsf{AC}^0$ Under Graphical Models cites this paper.

Learning $\mathsf{AC}^0$ Under Graphical Models Learning Juntas under Markov Random Fields

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:30:52.955246Z

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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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