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Paper Citation Record · LEDGER

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms

As of 7 August 2026, this Paper Citation Record lists 100 of 300 outbound references and 0 inbound Pith citation observations for arXiv:2607.02681.

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

pith.paper-citation-record.v1
2607.02681 v1

Coverage vector

measured 100 of 300 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T07:46:03.995262Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

100 of 300 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved98
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 70ac324c-173d-4fe6-8b5d-4bb7860f6355 · outbound

This paper cites 1996 , publisher=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms 1996 , publisher=

Reference 1

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Observation 6b576dec-171b-40ce-bf90-a65012b243c8 · outbound

This paper cites IEEE Transactions on Signal Processing , volume=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms IEEE Transactions on Signal Processing , volume=

Reference 2

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Observation a5dca471-f510-4243-960a-f1e096cbbde4 · outbound

This paper cites Information and Inference: A Journal of the IMA , volume=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Information and Inference: A Journal of the IMA , volume=

Reference 3

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Observation 68afcd29-7b64-45f9-83e6-cd6b4cacfbdd · outbound

This paper cites Optimal Cox regression under federated differential privacy: coefficients and cumulative hazards.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Optimal Cox regression under federated differential privacy: coefficients and cumulative hazards

Reference 4

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Observation 16a377db-a525-445e-81dc-5103c7355472 · outbound

This paper cites The Annals of Statistics , volume=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms The Annals of Statistics , volume=

Reference 5

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Observation 0b3ccee4-f751-47df-b53f-7b452f770d05 · outbound

This paper cites International Conference on Algorithmic Learning Theory , pages=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms International Conference on Algorithmic Learning Theory , pages=

Reference 6

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Observation 68dedd7a-3442-4bc7-8cd7-2dbf6772309a · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Advances in Neural Information Processing Systems , volume=

Reference 7

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Source-reported events for the cited work

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Observation 5422f4bf-a1fc-4348-b187-2f88eb3c338f · outbound

This paper cites 9th Innovations in Theoretical Computer Science Conference (ITCS 2018) , series =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms 9th Innovations in Theoretical Computer Science Conference (ITCS 2018) , series =

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:54d32f7cd7b25b48cdd3320b1868218a47204ffbde634fb27fc9406d2c582691

Observation fb2ffcad-ec08-493a-84a8-8089580c9ad1 · outbound

This paper cites Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing , pages =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing , pages =

Reference 9

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Observation a224de1b-bd9b-4cbc-9cec-8c0397632c37 · outbound

This paper cites Proceedings of the 37th International Conference on Machine Learning , series =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Proceedings of the 37th International Conference on Machine Learning , series =

Reference 10

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Observation a0fba210-2a4f-4169-b7f4-76306d3708fb · outbound

This paper cites Advances in Neural Information Processing Systems , volume =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Advances in Neural Information Processing Systems , volume =

Reference 11

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Observation a90763d1-bcd4-4c83-a08b-1d82c8a010f4 · outbound

This paper cites Proceedings of the 38th International Conference on Machine Learning , series =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Proceedings of the 38th International Conference on Machine Learning , series =

Reference 12

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Observation 66c36f9e-31bf-4ca8-86ea-112860b90095 · outbound

This paper cites Advances in Neural Information Processing Systems , volume =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Advances in Neural Information Processing Systems , volume =

Reference 13

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Observation 8f68a303-4fec-49b0-8652-7caccc376d08 · outbound

This paper cites The Thirty Seventh Annual Conference on Learning Theory , series =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms The Thirty Seventh Annual Conference on Learning Theory , series =

Reference 14

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Observation dc12ba8a-e1e5-4e0e-b03b-83aa861dca61 · outbound

This paper cites Journal of the Royal Statistical Society Series B: Statistical Methodology , pages=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Journal of the Royal Statistical Society Series B: Statistical Methodology , pages=

Reference 15

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Observation a793ab02-369a-4d1e-bcc3-35c0e271f28c · outbound

This paper cites Annual Review of Statistics and Its Application , volume=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Annual Review of Statistics and Its Application , volume=

Reference 16

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Observation c7e2c346-239e-4477-b85d-1852e5ed8565 · outbound

This paper cites A festschrift for Erich L.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms A festschrift for Erich L

Reference 17

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Observation eca75c4b-bc7e-4d0c-932c-813cc4e6d245 · outbound

This paper cites The Annals of Statistics , volume=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms The Annals of Statistics , volume=

Reference 18

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Observation 3f66015d-70b7-4b9d-b433-f79a149677f4 · outbound

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Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms The screening and ranking algorithm to detect

Reference 19

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Observation 0ee3e932-2b74-4006-a2f1-99df63685c05 · outbound

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Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 20

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Observation 839badbd-e36c-45b6-9f96-b3839ff27bdd · outbound

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Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Biometrika , publisher =

Reference 21

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Observation 97a20240-7849-4176-900a-c3a333028c04 · outbound

This paper cites Distance-based and continuum Fano inequalities with applications to statistical estimation.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Distance-based and continuum Fano inequalities with applications to statistical estimation

Reference 22

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Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms , author=

Reference 23

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Observation ac7fc4d1-9f5b-4d27-88c0-b1507fab58db · outbound

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Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms 30th USENIX Security Symposium (USENIX Security 21) , pages=

Reference 24

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Observation a4ee8de3-43a5-416b-81de-bdcb3d2f67f8 · outbound

This paper cites Advances in Neural Information Processing Systems 36 , year =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Advances in Neural Information Processing Systems 36 , year =

Reference 25

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:349ff74325311d5ed69724970983ff789185527fc751f8073c589284866f56fc

Observation b2e0ab1e-9c85-40f6-aa09-f2e1c7b97a13 · outbound

This paper cites 2019 , publisher=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms 2019 , publisher=

Reference 26

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Observation 1f4605ef-e0e1-4c1e-b7ea-a4ae589063a7 · outbound

This paper cites Multi-task Linear Regression without Eigenvalue Lower Bounds: Adaptivity, Robustness, and Safety.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Multi-task Linear Regression without Eigenvalue Lower Bounds: Adaptivity, Robustness, and Safety

Reference 27

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Observation cb9b0aa7-641c-43d7-864b-ef81d15be958 · outbound

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Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Robust Data Fusion via Subsampling

Reference 28

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Observation 0cb9cbc7-ef36-4277-a699-8a2ac0f12808 · outbound

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Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms arXiv preprint arXiv:2602.20698 , year =

Reference 29

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verified exact
arxiv_id, observed 2026-07-12T07:48:36.395954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e1ee1152-ed73-4a11-ab8f-e007f8fca920 · outbound

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Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Statistics and its Interface , volume=

Reference 30

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Observation 97c157f1-5f94-4127-b438-5b647cd853d1 · outbound

This paper cites Journal of the Royal Statistical Society Series B: Statistical Methodology , pages=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Journal of the Royal Statistical Society Series B: Statistical Methodology , pages=

Reference 31

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Observation a0725fbe-006f-44aa-b994-f37ccc204ab1 · outbound

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Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms 1980 , publisher=

Reference 32

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Observation 4fe05c4a-db7f-47b1-af3e-b32a83916242 · outbound

This paper cites Advances in Neural Information Processing Systems 37 , pages =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Advances in Neural Information Processing Systems 37 , pages =

Reference 33

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Observation 004de15c-1a9e-46e4-9865-89eb71b88038 · outbound

This paper cites The Thirty Eighth Annual Conference on Learning Theory , pages=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms The Thirty Eighth Annual Conference on Learning Theory , pages=

Reference 34

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Observation f209c99f-a534-419d-bcea-562ca530a6c8 · outbound

This paper cites Proceedings of the 2016 ACM SIGSAC conference on computer and communications security , pages=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Proceedings of the 2016 ACM SIGSAC conference on computer and communications security , pages=

Reference 35

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Observation c2ad21b6-2aa3-42fe-ada8-1c3cdb1de279 · outbound

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Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms 2017 , journal =

Reference 36

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Observation b050b776-db63-42be-af82-5b9c5bbe3ccc · outbound

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Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms 2017 IEEE Symposium on Security and Privacy (SP) , pages=

Reference 37

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:630b6d10576891a15f7748e877262cb9b80b327abb7c637ecbc77af75a8103ae

Observation d1a15730-0d80-4753-b5d1-0181c9e5cdcc · outbound

This paper cites Unified lower bounds for interactive high-dimensional estimation under information constraints.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unified lower bounds for interactive high-dimensional estimation under information constraints

Reference 38

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Observation 1ad3854e-bb15-4c1a-8dfe-aedfc446e7d5 · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 39

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:7d815f619bfece4f19c2dabb75ecfa27ae8b8afaba662de33fe46e269fbdcc34

Observation 1da44f9e-2628-4772-add8-b62c3f577557 · outbound

This paper cites Statistical analysis and forecasting of economic structural change , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Statistical analysis and forecasting of economic structural change , publisher =

Reference 40

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Source-reported events for the cited work

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:badb8c69cdffd19bb38cceface3235915b5557d4b96792472265fea71466adba

Observation b743e1ee-624f-4a72-9abc-90c2f908220b · outbound

This paper cites Finite Sample Differentially Private Confidence Intervals.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Finite Sample Differentially Private Confidence Intervals

Reference 41

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:dc933c583ecd3831d1adfeee95fc1474aec61c68cb0fbb4ed52cb9b56bbdc3e8

Observation 194d6885-66b7-4a49-bc31-c9efbb686638 · outbound

This paper cites Lecture Notes for ECE598YW (UIUC) , volume=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Lecture Notes for ECE598YW (UIUC) , volume=

Reference 42

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:8a3a52221f8df10ac8e531cef29f75e9667b4b9604f7e73089252cc986f8352b

Observation 5fd1a495-f42e-48c5-9b39-90a94598f303 · outbound

This paper cites Adversarial examples in the physical world.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Adversarial examples in the physical world

Reference 43

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:9129d99f637a61513bb04233240a492b9f10de42086247a7ea729a3589e6dbe0

Observation 210d5916-2c45-47ba-bed9-99c382a103f3 · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 44

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:a86dd6a40bdf5a65c701ad05d123ef71c973c7838298c5b99b766a2d6acb5773

Observation 525ce948-f98a-4dc2-af37-af4334262744 · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 45

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:d5cef894b74a638f27fe18bb17f3b23f9604699d376aa482c611000026901950

Observation 3d0a20c2-ea94-4f0a-8922-8976992af6fe · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 46

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:a46a89a4efc462906e38d642f41476c017d7821cf058b41b44e76d4392b7350f

Observation 6ee505be-b384-477b-abd6-1f8a55615046 · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 47

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:4e34bff60ae79cb549bf1d9d658a8fc2360990dfe92ead971424652b6c4465b1

Observation 8d378f33-2785-4f79-a994-31a1dc800f2e · outbound

This paper cites The Annals of Statistics , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms The Annals of Statistics , publisher =

Reference 48

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:6c49fc21db83a27a4a266a434b5855b87c3447939eef499f3c701117ce169e64

Observation da74646e-8ac4-46fd-a4b8-cee04a745b09 · outbound

This paper cites Multiscale.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Multiscale

Reference 49

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Source-reported events for the cited work

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:ab0ee8f75563fc851e6765e1206b425f683f693f67d0f7e69a4a812a435ac900

Observation 694d041e-70e0-4efb-be10-6c346bb42c75 · outbound

This paper cites The Annals of Statistics , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms The Annals of Statistics , publisher =

Reference 50

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:7a2eb0282e13e6876e82a6c3c65e89a3e94291ea0db5382f2fc537b1b588cb10

Observation ca1f6320-02f9-4e72-a507-40e237558f84 · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 51

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:51b5980ad1e6bbdbd0ef3604dceb7a15c24a3b95141621312ff518542ddb4560

Observation 15817dbd-bfaa-4bb6-a7ea-4b572c02e1fc · outbound

This paper cites Economic Structural Change , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Economic Structural Change , publisher =

Reference 52

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:d05e62c5187c9a1403143d75c3cd120045d5094143ead901e02c632e63f8a82a

Observation 39dc69a0-f8b7-4046-993c-10fe3c4cc65f · outbound

This paper cites Journal of the Royal Statistical Society: Series B (Statistical Methodology) , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Journal of the Royal Statistical Society: Series B (Statistical Methodology) , publisher =

Reference 53

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:a781b888313550e617e6b5e47367150e8f9e875ffb010ff80c4e63b30d5e9b7c

Observation a7de50c2-2cbe-45e6-86b9-c0d87de73298 · outbound

This paper cites Fast approximation of.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Fast approximation of

Reference 54

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:6e0245f947b3e5295beb69641609076bdbf5660d895284d003437731494ae098

Observation a731f18f-c185-4ee6-a7a1-72ac2efd1297 · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 55

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:83ef85d7d637fd8eb36f15522c28ee4709917c343bbf29eca66f1eb333faef18

Observation a99a773e-4ca9-4653-9968-f92610a0888b · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 56

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:e72e5608dedc2247eddc21084713becc03406c2187ed35c094f7d716f8792e1f

Observation 3662eea9-64a5-4fb7-934a-cb7f8312e80d · outbound

This paper cites Discrete Applied Mathematics , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Discrete Applied Mathematics , publisher =

Reference 57

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:831d9d4e532757f9e46629abd70c12c37fba826a173d51889ca99b80c13a8794

Observation a06da6d9-fc50-44a0-86e8-81298f201d06 · outbound

This paper cites Statistics & Probability Letters , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Statistics & Probability Letters , publisher =

Reference 58

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:188c5ef84ebbec9eb133f5e67b1cb95f2ff3226f6d90bc28a4e3074ad587cda1

Observation 8bbfe119-581d-4748-84de-23d161b597a2 · outbound

This paper cites International Conference on Artificial Intelligence and Statistics , pages =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms International Conference on Artificial Intelligence and Statistics , pages =

Reference 59

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:97a18ed57d5ee3de5f01c8c558c8bfe12db11b9d17e4f7f45fd5556941defe4f

Observation 2ce5e1c8-8a9a-4238-844d-0b0911d3a085 · outbound

This paper cites Summer School on Machine Learning , pages =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Summer School on Machine Learning , pages =

Reference 60

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:69327510ce2a19bddec3cbafe8147880d4ab1cad129bc6a204ce5cd3f1ace0e8

Observation 800140ac-dcb0-413e-b882-79cf6355bc34 · outbound

This paper cites The Annals of Statistics , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms The Annals of Statistics , publisher =

Reference 61

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:189238711d84177b1b5b78c3883d1869970b04b585c4334d88659605752f34cc

Observation 54108637-0203-442f-b7b1-b5af1916ddbe · outbound

This paper cites Statistica Sinica , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Statistica Sinica , publisher =

Reference 62

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:ebf29b41880cb83511503057d18559f512f55cdba8054a4e5c65430b7791d8c1

Observation a61aa1e5-c7f2-4255-8541-3fce51dbf29d · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 63

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:55d804d8402653fb972043ff5f9d2ddb309e59738523588be774742699a2286f

Observation 92590265-dd10-46b1-bb8d-dcb8d72e84f2 · outbound

This paper cites Journal of the American Statistical Association , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Journal of the American Statistical Association , publisher =

Reference 64

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:1e8e91a1bc307aa5e44ea6664cf8437b6ba9adfc0f537feb6cbace189a1765e5

Observation 7ecdfb74-694e-4823-baef-910055f30e55 · outbound

This paper cites Assouad,.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Assouad,

Reference 65

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:a5223ae1b87b203d2ec3d98629adb1c5f20d5ccadd2a685303aa8e253f1963af

Observation bad5fff7-aa22-4160-8137-45c174fb86b8 · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 66

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:cb9e474f09dbb84e337c32867e2e81ed87cda6265b86e4343465284fb1a9131b

Observation 23c3899a-5197-4fdf-b4d2-f0d1f6fa0446 · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 67

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:2492e700f134b75668d9916f41587fa5889c26bbdbf2303a41164b1370c04e49

Observation 5bbe510e-2383-4cba-9780-6bf4fb049ed2 · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 68

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:0a5308f1faf4d40f71ca0b111416d7d9b6a7f6e9d4561345dc1cab096b4a3ca0

Observation ee5a4ee7-c34b-40bc-bac8-a2c8faa4fe42 · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 69

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:81d2f91d871f72d601a6e5d0b69a276ffa654c27a48be61d198f2384d30abec8

Observation d08bd066-b67f-4c0e-ac83-7f959fc10136 · outbound

This paper cites Breakthroughs in statistics , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Breakthroughs in statistics , publisher =

Reference 70

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:9595f6ea5d68e4de248b52d00aa923c6085733d93379c65488f70f4e22265f78

Observation 89425c87-6509-4a66-b229-da80836e386e · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 71

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unresolved
no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:3a1871f6e98b9010d7c7022af77783de09a663f72295b640de996282bf0ad8ae

Observation 2dda367a-828e-4fb3-aaee-98ac94ce61bc · outbound

This paper cites Journal of the Royal Statistical Society: Series B (Statistical Methodology) , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Journal of the Royal Statistical Society: Series B (Statistical Methodology) , publisher =

Reference 72

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:465346ec6d1f5565b243115c8e9947bc4369d62f875b933b4751849fc4e90a49

Observation 457e33e4-5e09-44fe-bb57-41eb6e88c34b · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 73

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:9d44dd34a7b1328bcb6938b22c121bee07c8915c5836b2161ab7e8be59020ebd

Observation ccfda48e-99c1-4451-bf0e-edbb1f690d2d · outbound

This paper cites The Annals of Statistics , volume=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms The Annals of Statistics , volume=

Reference 74

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:b7432a3b12007c988fe078575dbb4051f220fe01e4f433f224f603abdbf8582a

Observation cc900a50-cc34-4d96-ba8c-74f491f7f23c · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 75

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:21199e8b2c3873a6dbbd5285928b35c39afaea3efaf7b6c2b2468868908e07d0

Observation 9c202e27-e34d-4903-93b8-c30274d74dcb · outbound

This paper cites International Conference on Artificial Intelligence and Statistics , pages=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms International Conference on Artificial Intelligence and Statistics , pages=

Reference 76

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:85002797b136344dabf60383d48050c229873deb9b3b868cfbc84a5180c9f0a1

Observation ab57712d-bf56-4df5-b515-f90688b0bbf8 · outbound

This paper cites Department of Statistics, Princeton University , year=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Department of Statistics, Princeton University , year=

Reference 77

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:8130b3c675b43cf9ec2570bd10a618b2408dc938eb442e7264e9305f859d5a0a

Observation 0cff1146-3b93-4267-b18c-94c77a0fbbb8 · outbound

This paper cites Conference on Learning Theory , pages=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Conference on Learning Theory , pages=

Reference 78

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no resolver link, observed 2026-07-12T07:46:03.995262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:a875f4aea019e2eb94f5b269efb42ed788bf006bc1722f1e17387c5e00c8d440

Observation 1421cd51-1194-466b-9e10-c47eb7e6bd42 · outbound

This paper cites Proceedings of the International Congress of Mathematicians, Vancouver, 1975 , volume=.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Proceedings of the International Congress of Mathematicians, Vancouver, 1975 , volume=

Reference 79

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:1cdf2ecceadf1b19a139a0aa9ecd219d169c795ab60fb3366501200b37d7d91a

Observation f8dd4b9b-96c0-4ce3-95aa-83b723e71186 · outbound

This paper cites A general decision theory for.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms A general decision theory for

Reference 80

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Source-reported events for the cited work

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Observation 78ac313e-0b89-468a-a4c7-d19db1f9a126 · outbound

This paper cites International Conference on Machine Learning , pages =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms International Conference on Machine Learning , pages =

Reference 81

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Observation 2a1558cc-fca1-4a2d-8f46-0632a0b67a1c · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 82

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Observation 9fb852d8-e0ce-49ff-ac84-951a73106b36 · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 83

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Observation a94cb29a-9fc2-4e9d-bd5b-6c4f1df9235e · outbound

This paper cites Journal of the American Statistical Association , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Journal of the American Statistical Association , publisher =

Reference 84

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Observation 0e0a3a4c-ffb6-4b53-949e-c2d741b0a62b · outbound

This paper cites Circular binary segmentation for the analysis of array-based.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Circular binary segmentation for the analysis of array-based

Reference 85

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Observation 688f5e45-295b-4d72-9a46-6915959aa612 · outbound

This paper cites Journal of applied meteorology and climatology , volume = 46, number = 6, pages =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Journal of applied meteorology and climatology , volume = 46, number = 6, pages =

Reference 86

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Observation 430029eb-caf4-4fd2-ba30-81a8a10ce8a0 · outbound

This paper cites Journal of Climate , volume = 26, number = 14, pages =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Journal of Climate , volume = 26, number = 14, pages =

Reference 87

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Observation fa3fa6c5-2594-4dbc-afdb-e1864daa91cf · outbound

This paper cites Stat , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Stat , publisher =

Reference 88

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Observation 7e757ac3-9756-487c-bf95-714cd19c36e7 · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 89

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:6669892521effbd825bec8e3ec3e282025e0d4b2f0231c672b8db5e3f23594e2

Observation cb77666a-08e5-4a6e-8840-61f90ceb7404 · outbound

This paper cites The Journal of Finance , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms The Journal of Finance , publisher =

Reference 90

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Observation 16ec275f-88ba-4a40-a1c6-687d0c30fb1f · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 91

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:86ec15d38a64b5bb5097ffcc4d3fba7c6da47b99d07f244eecb085f1ea5c4b82

Observation 614b549e-9b8f-4f7e-a27d-d11f9edd7acc · outbound

This paper cites Robustness and Complex Data Structures , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Robustness and Complex Data Structures , publisher =

Reference 92

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:cf672c985dace2b499a281d0878be80b97965c297f9d9ecc5af021125cc6feaa

Observation 49da2a31-c34c-46af-935c-850b89742f73 · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 93

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:a551b0d4a1bd96f6eb43a46ac6b380c415e58cd6c300b7a2ab7ca19bc755451d

Observation 42b56055-eb5f-4c1d-a641-e57aee31d28c · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 94

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:35b2d009f887cf1c8432e98a14582575fef2f2916e0dcf02e3bcb235c3be8fa2

Observation dccf541d-4d91-48e6-b67a-54b8f89409f4 · outbound

This paper cites Annals of Statistics , publisher =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Annals of Statistics , publisher =

Reference 95

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:47552b952984b234122cd8d501294877c59f96c6350ffce0d83c6031ae776baf

Observation f47638f7-ddf0-4443-81a3-64b82e519986 · outbound

This paper cites 2018 , howpublished =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms 2018 , howpublished =

Reference 96

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:f598a27f20352691e11c6186023a040149546bd1a47ba44c6ab51e966806c1d6

Observation 44120f39-cd5e-46c5-85ab-96f5159d1d92 · outbound

This paper cites A private and computationally-efficient estimator for unbounded.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms A private and computationally-efficient estimator for unbounded

Reference 97

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:088d594153be49c7ba0e1339994c81a0e9b576b16058a9a324dfcbdaf60098ad

Observation a29edb8d-11e2-4ccf-ac76-3c0947be8115 · outbound

This paper cites an unresolved cited work.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Unresolved cited work

Reference 98

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:b8df8db6f2bae65952f20efbfc7b091683fc773aabba636d3ae6973517836697

Observation 0e65c48e-ea75-4d6f-a094-949de3fbc0ff · outbound

This paper cites IEEE Transactions on Information Theory , volume = 68, number = 1, pages =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms IEEE Transactions on Information Theory , volume = 68, number = 1, pages =

Reference 99

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:707e77271c21157416b4617e7a34022aae131deb2a70bb4462fe1d68bd542273

Observation 0a2b2b0d-1cfd-40ea-b6ca-9b4a4fd89c35 · outbound

This paper cites Annales de l'ISUP , volume = 63, pages =.

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms Annales de l'ISUP , volume = 63, pages =

Reference 100

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source=arxiv_source observed=2026-07-12T07:46:03.995262Z digest=sha256:f01e671868f51eb208869b8a9b84b6d73c1faed9e67c7c41d2db7290c185ba41

Pith citing papers

No inbound Pith citation observations are available.