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Paper Citation Record · LEDGER

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set

As of 11 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2607.23679.

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

pith.paper-citation-record.v1
2607.23679 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-30T16:14:14.806220Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

50 of 50 outbound references displayed

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External citation measurements

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Outbound references

Observation dacc8228-c44c-4282-b494-dd3430b1ed2b · outbound

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

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Advances in Neural Information Processing Systems , volume=

Reference 1

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source=arxiv_source observed=2026-07-30T16:14:09.363479Z digest=sha256:99728d44f00e2e0563b8012c5f4ef0e82c08d98e166b97c04ded4f5c24b564aa

Observation 42620710-85bf-468f-9bdc-2035cc0e3737 · outbound

This paper cites 1986 , isbn =.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set 1986 , isbn =

Reference 2

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source=arxiv_source observed=2026-07-30T16:14:09.416205Z digest=sha256:d9bf4ac7cd44210ad13b29c04d09b58e09b0650040f2cc56d4c93e20f7f93c59

Observation da022341-15f9-424b-a8a9-aca08d18137f · outbound

This paper cites , title =.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set , title =

Reference 3

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source=arxiv_source observed=2026-07-30T16:14:09.545452Z digest=sha256:f589a26e04db253dc88ecdfb9eb506874f8fab66a0bebafb840c88c2e5489987

Observation 1eb522b2-b8d2-45ad-a82f-233d74fad036 · outbound

This paper cites , title =.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set , title =

Reference 4

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source=arxiv_source observed=2026-07-30T16:14:09.635036Z digest=sha256:0b1eb74335eb92a99caa66a5cd13bcc715c146301bb7a1e6e4b56f88c1b9ebc8

Observation 32ad44ef-f0a4-4b34-ae0c-515f666c5766 · outbound

This paper cites Proceedings of the 18th Annual IEEE Symposium on Foundations of Computer Science (FOCS) , year =.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Proceedings of the 18th Annual IEEE Symposium on Foundations of Computer Science (FOCS) , year =

Reference 5

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Observation def4efb4-2c23-43c0-8cdb-272e0cf00306 · outbound

This paper cites Proceedings of the 24th Annual IEEE Symposium on Foundations of Computer Science (FOCS) , year =.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Proceedings of the 24th Annual IEEE Symposium on Foundations of Computer Science (FOCS) , year =

Reference 6

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source=arxiv_source observed=2026-07-30T16:14:09.891139Z digest=sha256:95fd55996f4fbc23dbf8e4ef7f9b48e0eb940c46eab5451a4ca41251e023b883

Observation e8334492-87ab-40fa-9095-c53f795a3bbe · outbound

This paper cites 1995 , isbn =.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set 1995 , isbn =

Reference 7

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source=arxiv_source observed=2026-07-30T16:14:10.027441Z digest=sha256:7c8d82af6051ce47fff49e349e62639fee07d41c42da6b0d4b8b1d90eebb6e11

Observation 1309f5e2-fbc8-4d68-855e-098a0b03c6d4 · outbound

This paper cites Festschrift for Lucien Le Cam: Research Papers in Probability and Statistics , editor =.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Festschrift for Lucien Le Cam: Research Papers in Probability and Statistics , editor =

Reference 8

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source=arxiv_source observed=2026-07-30T16:14:10.146743Z digest=sha256:91078654b6a79c99ee4434793da5cd45a7d40c162d1051d5ef8780a9cbded924

Observation 06eb3411-ef40-4077-85e4-afffb9844d74 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 9

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source=arxiv_source observed=2026-07-30T16:14:10.284275Z digest=sha256:b06632b0589b9365fc1ec70e26bb70dc4a9697f8f7f74d8bebd44ac3bc18455f

Observation 62e93617-6fae-4418-a90c-d955a6ba39f6 · outbound

This paper cites Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing , pages=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing , pages=

Reference 10

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source=arxiv_source observed=2026-07-30T16:14:10.346575Z digest=sha256:c265bbc2387153dc1ef70d5749f14b7503762ef4417631ba7ff12d734388a6fe

Observation 63bcf09f-0f1a-4b14-be1e-a2047b184ce1 · outbound

This paper cites 2020 , publisher=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set 2020 , publisher=

Reference 11

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Observation 56eb6e71-6062-47fb-85f3-72f7433487f5 · outbound

This paper cites 2024 , eprint=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set 2024 , eprint=

Reference 12

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Observation 1706c50c-7ed8-4f49-bd52-94e060d39cb7 · outbound

This paper cites the Annals of Probability , pages=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set the Annals of Probability , pages=

Reference 13

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source=arxiv_source observed=2026-07-30T16:14:10.818082Z digest=sha256:8b86d1edd9de8c53ca6ade0e7c9e541ed02c753172ddb9f902881e41eb113850

Observation 306f28f2-03ef-4d59-9b25-afd182eed91a · outbound

This paper cites Conference on Learning Theory , pages=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Conference on Learning Theory , pages=

Reference 14

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Observation 77362e5b-c935-4ed5-9720-a25d71665321 · outbound

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

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set The Thirty Sixth Annual Conference on Learning Theory , pages=

Reference 15

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source=arxiv_source observed=2026-07-30T16:14:11.149571Z digest=sha256:4f80376f94c9efff7f39f6e2db5706796255058be714b0cb92cf183d221e505e

Observation 9bcac921-6d29-4d25-b572-25c3e21aa881 · outbound

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

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Advances in Neural Information Processing Systems , volume=

Reference 16

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Observation a3e6c841-1f68-4b78-bacb-f6d287abf51b · outbound

This paper cites The Thirteenth International Conference on Learning Representations , year=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set The Thirteenth International Conference on Learning Representations , year=

Reference 17

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Observation 9ac82543-d35a-4aa4-a0c9-3dd998d8e8c5 · outbound

This paper cites Advances in neural information processing systems , volume=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Advances in neural information processing systems , volume=

Reference 18

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Observation a534ec07-0ed4-4f35-a9f5-608e74eb494a · outbound

This paper cites Advances in neural information processing systems , volume=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Advances in neural information processing systems , volume=

Reference 19

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Observation 2640db3d-bb7b-4e4c-ba08-1e14aa7b408c · outbound

This paper cites 1998 , publisher=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set 1998 , publisher=

Reference 20

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source=arxiv_source observed=2026-07-30T16:14:11.607012Z digest=sha256:3d56efbfc7b13de901b2e54e41a78f726826f6f933fe4b6e781ae3ea05382d03

Observation 6a7818e6-d46c-448f-bdaf-2869f4971ef4 · outbound

This paper cites Artificial Intelligence and Statistics , pages=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Artificial Intelligence and Statistics , pages=

Reference 21

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Observation 8f0583fd-3f28-4cf2-8839-16a45d85afa9 · outbound

This paper cites Variance-Dependent Regret Lower Bounds for Contextual Bandits.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Variance-Dependent Regret Lower Bounds for Contextual Bandits

Reference 22

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Observation b1b5da5b-cb52-4fc8-9872-3f1696a729a9 · outbound

This paper cites Conference On Learning Theory , pages=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Conference On Learning Theory , pages=

Reference 23

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Observation f729322c-b2a4-4a15-8c54-66e0af4148a2 · outbound

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

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Advances in Neural Information Processing Systems , volume=

Reference 24

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Observation 552dc51f-4d5a-4ee7-8816-bce49e485c87 · outbound

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

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Advances in Neural Information Processing Systems , volume=

Reference 25

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Observation 1355f1cd-0755-4ddb-90f6-2a9bac3fb19b · outbound

This paper cites Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs

Reference 26

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Observation fcb8e8a6-2baf-4b57-934f-04161845beb7 · outbound

This paper cites 21st Annual Conference on Learning Theory , number=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set 21st Annual Conference on Learning Theory , number=

Reference 27

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Observation f82a2e4b-41a3-4a85-bf8e-b2c348f0d7e1 · outbound

This paper cites 2004 , publisher=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set 2004 , publisher=

Reference 28

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Observation 7cd50da5-255d-4c9d-8881-385b2e0fd8aa · outbound

This paper cites Do we need to estimate the variance in robust mean estimation?.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Do we need to estimate the variance in robust mean estimation?

Reference 29

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Observation 79dc87cf-ff6c-4b9c-86c3-477b03f512c9 · outbound

This paper cites Transactions on Machine Learning Research , year =.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Transactions on Machine Learning Research , year =

Reference 30

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Observation 8bff835a-eed4-49f2-8ba2-a5d7afcac431 · outbound

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Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Machine learning , volume=

Reference 31

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source=arxiv_source observed=2026-07-30T16:14:12.546453Z digest=sha256:17258190fce544984d8a00c2207459bba7fce239066d86f00f07c063ec1e01e4

Observation 2e7645f5-555a-4f9c-889c-d1d66a80d82b · outbound

This paper cites Minimax Policies for Adversarial and Stochastic Bandits , booktitle =.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Minimax Policies for Adversarial and Stochastic Bandits , booktitle =

Reference 32

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Observation ed5cd5dc-f377-4156-9830-82e6e37a905c · outbound

This paper cites A Minimax and Asymptotically Optimal Algorithm for Stochastic Bandits , booktitle =.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set A Minimax and Asymptotically Optimal Algorithm for Stochastic Bandits , booktitle =

Reference 33

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Observation 5b67dfe1-2f0a-4fe6-a2ff-e92268bedf4a · outbound

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

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set International Conference on Machine Learning , pages =

Reference 34

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Observation 58529fcd-3f6a-4e35-a921-0f57a564ce80 · outbound

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

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set International Conference on Machine Learning , pages =

Reference 35

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Observation 38835b35-b1c9-40ce-968f-a92d4798eed9 · outbound

This paper cites International conference on machine learning , pages=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set International conference on machine learning , pages=

Reference 36

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Observation 6a52458e-2a5f-4457-b21e-d4d944c7ca9b · outbound

This paper cites IEEE Transactions on Information Theory , volume=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set IEEE Transactions on Information Theory , volume=

Reference 37

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source=arxiv_source observed=2026-07-30T16:14:13.459637Z digest=sha256:d463e1d187b99be7628d83aca0a2f0ba1d66eef2634c88d75e7a8ea087836f63

Observation 73bcd797-8c32-428e-9b8e-4909fef56845 · outbound

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

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set International Conference on Machine Learning , pages=

Reference 38

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source=arxiv_source observed=2026-07-30T16:14:13.549518Z digest=sha256:2df2011753f0003af848db7f884d67cbd5282dd70bae6d62368294d4c475d983

Observation 0faa6b90-518c-4559-96bc-f00735c1b7ec · outbound

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

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Advances in Neural Information Processing Systems , volume=

Reference 39

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no resolver link, observed 2026-07-30T16:14:13.671741Z

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source=arxiv_source observed=2026-07-30T16:14:13.671741Z digest=sha256:4448c1185392982bda787819cbe8864584cc7b523cbcfa39e58e8eab5c9891e9

Observation d9beab0e-b81b-4658-8cf8-cec3f49ee13f · outbound

This paper cites Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs

Reference 40

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no resolver link, observed 2026-07-30T16:14:13.761525Z

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source=arxiv_source observed=2026-07-30T16:14:13.761525Z digest=sha256:60350fe1f275dc92ae2d141c72ed04aa9a07a9f8dbf6a5a76c13e2a2f0cfdc2b

Observation 904e2ad9-42a7-40a1-9311-50713f61c8c9 · outbound

This paper cites Proceedings of the fourteenth international conference on artificial intelligence and statistics , pages=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Proceedings of the fourteenth international conference on artificial intelligence and statistics , pages=

Reference 41

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no resolver link, observed 2026-07-30T16:14:13.860087Z

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source=arxiv_source observed=2026-07-30T16:14:13.860087Z digest=sha256:0964982a01e5182a42667f862c17782c31093f92e6941eee4da2766c8e3c3bfa

Observation f0207830-3764-49a2-9639-7dfa0cd0c225 · outbound

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

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Advances in Neural Information Processing Systems , volume=

Reference 42

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no resolver link, observed 2026-07-30T16:14:13.985634Z

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source=arxiv_source observed=2026-07-30T16:14:13.985634Z digest=sha256:ed82a36ea0ba8cec5295c27dd271c370e3ba466fa29a456206d1609948a948dd

Observation 8891bb5a-1d11-445f-bf00-a17dc0763b0d · outbound

This paper cites Forty-second International Conference on Machine Learning , year=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Forty-second International Conference on Machine Learning , year=

Reference 43

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no resolver link, observed 2026-07-30T16:14:14.103314Z

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source=arxiv_source observed=2026-07-30T16:14:14.103314Z digest=sha256:46659b2627099d69423cc0b09795f0e9dd0d33511a4c73379ee3e9bb16619cf2

Observation 4479ee79-858e-47f0-8133-9407ff5ca78f · outbound

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

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set International Conference on Machine Learning , pages=

Reference 44

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no resolver link, observed 2026-07-30T16:14:14.204419Z

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source=arxiv_source observed=2026-07-30T16:14:14.204419Z digest=sha256:1742cb847d102e58ef3249e74074ef42b24e29ded23f92f916eab177251aae76

Observation c3767297-0b0a-45de-8e61-f654ab6db284 · outbound

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

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set International Conference on Machine Learning , pages=

Reference 45

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no resolver link, observed 2026-07-30T16:14:14.319133Z

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source=arxiv_source observed=2026-07-30T16:14:14.319133Z digest=sha256:cf388eea78bb95be787e4ca6e65ea6f833cf36b37a0486de0db5a26f46472cfb

Observation 8cf4a89c-4175-4091-b72b-4b1531b122ec · outbound

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

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Advances in Neural Information Processing Systems , volume=

Reference 46

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no resolver link, observed 2026-07-30T16:14:14.403271Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-07-30T16:14:14.403271Z digest=sha256:7ac1a5d9226c9d7a2cee403c2b63b2a2d4704eb9079aabef351ec919737b09bf

Observation 23c994f3-366d-4fdb-9130-075863eca5d5 · outbound

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

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set International Conference on Machine Learning , pages=

Reference 47

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no resolver link, observed 2026-07-30T16:14:14.498250Z

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source=arxiv_source observed=2026-07-30T16:14:14.498250Z digest=sha256:f65da725f964d8d594463305d0487f9f8c8733c87a92e733a05752faebef3396

Observation 0fe1e75e-c688-40d1-a69c-ab5acbaef3a9 · outbound

This paper cites The Thirteenth International Conference on Learning Representations , year=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set The Thirteenth International Conference on Learning Representations , year=

Reference 48

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no resolver link, observed 2026-07-30T16:14:14.634392Z

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source=arxiv_source observed=2026-07-30T16:14:14.634392Z digest=sha256:ca091c8077b3774eef12d6f7bcf2f984f8d25036883f64377feb37dc411f3539

Observation 7b2ce430-fc05-42c6-88a4-a72b9fc2d9ec · outbound

This paper cites arXiv preprint arXiv:2508.02103 , year=.

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set arXiv preprint arXiv:2508.02103 , year=

Reference 49

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no resolver link, observed 2026-07-30T16:14:14.722986Z

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source=arxiv_source observed=2026-07-30T16:14:14.722986Z digest=sha256:4976544a581c90fd55a4a9d0977860ffdedba0f640fc6120b9db257e92f5a953

Observation feede862-ad74-48ec-84aa-bdd710b9a32b · outbound

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

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set International Conference on Machine Learning , pages=

Reference 50

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source=arxiv_source observed=2026-07-30T16:14:14.806220Z digest=sha256:17b6908d99d11e2faac63fa23d38b00b1cd6dc937ec924bf0dfb27fe51aee56c

Pith citing papers

No inbound Pith citation observations are available.