Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities | Paper Citation Record

Observation b50434a5-1e5a-489f-b484-5d373aad2348 · outbound

This paper cites Egger, Bruce G.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Egger, Bruce G

Reference 1

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Observation aead1176-b91a-4540-bd36-5979a1a1a2b7 · outbound

This paper cites A Dynamic Near-Optimal Algorithm for Online Linear Programming.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities A Dynamic Near-Optimal Algorithm for Online Linear Programming

Reference 2

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Observation cb57f87b-88ae-447f-94fb-0a1226845234 · outbound

This paper cites More Asymmetry Yields Faster Matrix Multiplication.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities More Asymmetry Yields Faster Matrix Multiplication

Reference 3

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Observation 7d6c33e5-4166-4ceb-a1a3-611c52d5e3d3 · outbound

This paper cites Improvements in Quantum SDP-Solving with Applications.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Improvements in Quantum SDP-Solving with Applications

Reference 4

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Observation 363ae98f-84cb-419f-a25b-cf97dd33a24a · outbound

This paper cites Quantum algorithms for zero-sum games.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum algorithms for zero-sum games

Reference 5

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Observation 368a4336-d2e6-41b9-b816-862869efbedd · outbound

This paper cites Quantum SDP-Solvers: Better upper and lower bounds.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum SDP-Solvers: Better upper and lower bounds

Reference 6

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Observation eaf6fed4-ad20-4b5b-bf1e-50d19dec9e63 · outbound

This paper cites Convex optimization using quantum oracles.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Convex optimization using quantum oracles

Reference 7

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Observation 07562579-caff-4959-813d-12b689044aec · outbound

This paper cites Schapire, The nonstochastic multiarmed bandit problem, SIAM Journal on Computing 32 (2002), no.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Schapire, The nonstochastic multiarmed bandit problem, SIAM Journal on Computing 32 (2002), no

Reference 8

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Observation 699bf608-cbd1-4cf1-937b-4dba32210c4e · outbound

This paper cites Fast Convex Optimization with Quantum Gradient Methods.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Fast Convex Optimization with Quantum Gradient Methods

Reference 9

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Observation 642124cf-93f1-4751-b970-3a4440b17d37 · outbound

This paper cites A quantum central path algorithm for linear optimization.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities A quantum central path algorithm for linear optimization

Reference 10

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Observation 726a1259-e5f7-4e70-87f8-475ea116b13b · outbound

This paper cites Quantum Interior Point Methods for Semidefinite Optimization.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum Interior Point Methods for Semidefinite Optimization

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:57:44.167326Z

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Observation cb0ff5ab-43ba-43fe-8cc0-960f249207de · outbound

This paper cites Bandits with Knapsacks.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Bandits with Knapsacks

Reference 12

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Observation 120be4e4-6211-420c-bf20-f51026067f9f · outbound

This paper cites 1, 80–90.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities 1, 80–90

Reference 13

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Observation 20493e5b-e624-4840-8aa1-87911a58ca39 · outbound

This paper cites 6, 1537–1550.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities 6, 1537–1550

Reference 14

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Observation 7419499d-400c-4418-9ef9-19e9b6a77577 · outbound

This paper cites Borkar and Sean P.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Borkar and Sean P

Reference 15

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Observation 33c3fc9f-1c35-4315-960e-1f0142165929 · outbound

This paper cites Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:57:43.991458Z

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Observation 880afff6-a802-440b-8e42-bc34575da4be · outbound

This paper cites Boyd and Lieven Vandenberghe, Convex optimization , Cambridge University Press, 2004.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Boyd and Lieven Vandenberghe, Convex optimization , Cambridge University Press, 2004

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:48.962047Z

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Observation 0696eb8a-29dd-4ab3-8adb-5a626ee15282 · outbound

This paper cites Minimum Cost Flows, MDPs, and $\ell_1$-Regression in Nearly Linear Time for Dense Instances.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Minimum Cost Flows, MDPs, and $\ell_1$-Regression in Nearly Linear Time for Dense Instances

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:57:43.914073Z

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Observation 566b3d9f-7eb3-4d6f-966d-5aa6217d6578 · outbound

This paper cites Quantum SDP Solvers: Large Speed-ups, Optimality, and Applications to Quantum Learning.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum SDP Solvers: Large Speed-ups, Optimality, and Applications to Quantum Learning

Reference 19

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Observation 602d7ebc-f86c-441b-9a98-6c0894387f2f · outbound

This paper cites Quantum Speed-ups for Semidefinite Programming.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum Speed-ups for Semidefinite Programming

Reference 20

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Observation fe7baeaf-9487-4a7a-aa76-691c1eec0fb5 · outbound

This paper cites Quantum Amplitude Amplification and Estimation.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum Amplitude Amplification and Estimation

Reference 21

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Observation 8324d44d-4eae-452a-9e92-a0aa89568a9c · outbound

This paper cites Quantum algorithms and lower bounds for convex optimization.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum algorithms and lower bounds for convex optimization

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:57:43.739225Z

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Observation af7eb1e4-b995-428e-a3dd-58365c5a57f2 · outbound

This paper cites Quantum Langevin Dynamics for Optimization.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum Langevin Dynamics for Optimization

Reference 23

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Observation e0aa1d8f-700d-40ab-ad32-9a8166f09574 · outbound

This paper cites Solving Linear Programs in the Current Matrix Multiplication Time.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Solving Linear Programs in the Current Matrix Multiplication Time

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:57:43.505172Z

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Observation ef862e27-8914-4d58-b85f-2a7442031f89 · outbound

This paper cites Near-Optimal Quantum Algorithms for Multivariate Mean Estimation.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Near-Optimal Quantum Algorithms for Multivariate Mean Estimation

Reference 25

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T19:57:43.359849Z

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Observation e720fe25-027c-45e2-b7c8-f3d6e0bf0b83 · outbound

This paper cites Quantum Bayesian Optimization.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum Bayesian Optimization

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:57:43.279714Z

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Observation 4e430bb2-99a6-4e24-a458-55cff99ecabd · outbound

This paper cites Dantzig and Mukund N.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Dantzig and Mukund N

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:48.830416Z

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Observation 8036f4d6-34e7-4b67-abd7-e98a3c604085 · outbound

This paper cites Briegel, Machine learning & artificial intelligence in the quantum domain: a review of recent progress, Reports on Progress in Physics 81 (2018), no.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Briegel, Machine learning & artificial intelligence in the quantum domain: a review of recent progress, Reports on Progress in Physics 81 (2018), no

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:48.661263Z

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Observation 3bdda9b6-fb21-4c25-880c-f4c9f6eaba25 · outbound

This paper cites 6, 1586–1602.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities 6, 1586–1602

Reference 29

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Observation 8d8efd20-f15a-49d5-a2a2-5f5ff0bf81c7 · outbound

This paper cites Schapire, A decision-theoretic generalization of on-line learning and an application to boosting, Journal of Computer and System Sciences 55 (1997), no.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Schapire, A decision-theoretic generalization of on-line learning and an application to boosting, Journal of Computer and System Sciences 55 (1997), no

Reference 30

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Observation 56fc6754-e37a-42f8-a091-83e6cd889781 · outbound

This paper cites Logarithmic-Regret Quantum Learning Algorithms for Zero-Sum Games.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Logarithmic-Regret Quantum Learning Algorithms for Zero-Sum Games

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:57:43.122680Z

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Observation 5f1025c3-546f-4352-a0e3-ff193b9c0596 · outbound

This paper cites Quantum random access memory.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum random access memory

Reference 32

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Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Unresolved cited work

Reference 33

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Observation 4b35a058-4115-4652-8f88-f9028a9b4af4 · outbound

This paper cites Robustness of Quantum Algorithms for Nonconvex Optimization.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Robustness of Quantum Algorithms for Nonconvex Optimization

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:57:42.957849Z

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Observation 753acd52-4bc3-4218-b7ce-999bfb0c17e9 · outbound

This paper cites Grigoriadis and Leonid G.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Grigoriadis and Leonid G

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:47.977746Z

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Observation 35e2588e-4179-4b71-8649-83da9d6630a2 · outbound

This paper cites Creating superpositions that correspond to efficiently integrable probability distributions.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Creating superpositions that correspond to efficiently integrable probability distributions

Reference 36

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Observation 90eaa6b8-db85-4660-a19e-3afd0727b252 · outbound

This paper cites Quantum policy gradient algorithms.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum policy gradient algorithms

Reference 37

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Observation 32424d26-0a4a-4623-9aca-1f855878f47f · outbound

This paper cites Faster Dynamic Matrix Inverse for Faster LPs.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Faster Dynamic Matrix Inverse for Faster LPs

Reference 38

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Observation b82d9ebd-6ef5-425f-aae5-a8cbcf619435 · outbound

This paper cites 302–311, 1984.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities 302–311, 1984

Reference 39

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Observation b23b6656-9735-4c60-9182-7ae5e06d36b5 · outbound

This paper cites Quantum Recommendation Systems.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum Recommendation Systems

Reference 40

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Observation eaae0e5c-31b7-42b0-acdd-5c95a2212601 · outbound

This paper cites an unresolved cited work.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Unresolved cited work

Reference 41

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Observation e7a28ad8-b0fb-4ba2-b565-ae8b821b7069 · outbound

This paper cites Mean estimation when you have the source code; or, quantum Monte Carlo methods.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Mean estimation when you have the source code; or, quantum Monte Carlo methods

Reference 42

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Observation 68f5c6b7-2993-4cfd-80c5-4a8dc2a45166 · outbound

This paper cites 1029–1046, SIAM, 2018.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities 1029–1046, SIAM, 2018

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:47.403029Z

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Observation 92bc1cc8-1ec0-4444-85e1-844f755c1879 · outbound

This paper cites Efficient Inverse Maintenance and Faster Algorithms for Linear Programming.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Efficient Inverse Maintenance and Faster Algorithms for Linear Programming

Reference 44

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T19:57:42.777190Z

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Observation b7f9aa8c-54b5-4756-ad01-46e5b385f453 · outbound

This paper cites A Faster Cutting Plane Method and its Implications for Combinatorial and Convex Optimization.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities A Faster Cutting Plane Method and its Implications for Combinatorial and Convex Optimization

Reference 45

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Observation 64f18676-65ab-453b-a89c-578571d5fd16 · outbound

This paper cites Quantum Hamiltonian Descent.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum Hamiltonian Descent

Reference 46

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Observation 36d37678-7952-40d2-a8ba-8222cac6e1d4 · outbound

This paper cites (Sub)Exponential Quantum Speedup for Optimization.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities (Sub)Exponential Quantum Speedup for Optimization

Reference 47

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Observation 8a4e52cc-4297-444f-9833-cbc98e3e5243 · outbound

This paper cites The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with Knapsacks.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with Knapsacks

Reference 48

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T19:57:42.455393Z

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Observation 937891b8-a8a1-47ac-94b6-df38fa874f12 · outbound

This paper cites On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:57:42.299439Z

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Observation 8a713f1e-a2a9-4585-b7e5-4f2e3b23a94e · outbound

This paper cites 6, 305–308.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities 6, 305–308

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:47.246916Z

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Observation 2c9a037a-b20f-42fd-8375-f0a3759256fa · outbound

This paper cites 5, 22–es.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities 5, 22–es

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:47.093969Z

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Observation 1bc370a5-53fc-401b-8024-4ad470453a1e · outbound

This paper cites A Survey on Quantum Reinforcement Learning.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities A Survey on Quantum Reinforcement Learning

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T19:57:39.379508Z

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Observation 1cd574c6-701e-4ff5-9ead-bc4e252d9154 · outbound

This paper cites Quantum speedup of Monte Carlo methods.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum speedup of Monte Carlo methods

Reference 53

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Observation 76481467-2506-4291-b0b1-372e30d7a8ea · outbound

This paper cites Fast quantum subroutines for the simplex method.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Fast quantum subroutines for the simplex method

Reference 54

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T19:57:42.125165Z

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Observation 6bdb3dc7-91a7-4ee8-89c6-d26b2549abac · outbound

This paper cites 5, 527–535.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities 5, 527–535

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:46.932157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 45abe258-3fe8-4d3b-b62c-7828c2c65d88 · outbound

This paper cites an unresolved cited work.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:57:46.758369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cf02df83-950a-48ff-868b-55f209a71297 · outbound

This paper cites Introduction to Multi-Armed Bandits.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Introduction to Multi-Armed Bandits

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-06T19:57:39.842671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 903e563b-539a-47a2-9e62-335fbf81979d · outbound

This paper cites Quantum Multi-Armed Bandits and Stochastic Linear Bandits Enjoy Logarithmic Regrets.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum Multi-Armed Bandits and Stochastic Linear Bandits Enjoy Logarithmic Regrets

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:57:41.969116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5898810d-84a1-4297-b12a-40d6aeeb1623 · outbound

This paper cites Quantum exploration algorithms for multi-armed bandits.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum exploration algorithms for multi-armed bandits

Reference 59

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:57:41.856421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0ff8b488-8263-4c52-928c-46787f052a43 · outbound

This paper cites 2, 517–546.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities 2, 517–546

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:46.620183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 47accc2e-042c-4ccf-85e1-ec3920efb695 · outbound

This paper cites an unresolved cited work.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Unresolved cited work

Reference 61

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:57:46.423043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ab49cd41-d494-4232-a40e-3fba1b88046c · outbound

This paper cites 3, 737–757.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities 3, 737–757

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:46.285976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4f571398-1d1a-4e6d-ad4b-389ac2cf242c · outbound

This paper cites Quantum Lower Bounds for Finding Stationary Points of Nonconvex Functions.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Quantum Lower Bounds for Finding Stationary Points of Nonconvex Functions

Reference 63

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T19:57:41.716828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d52ee81a-1db6-4ab8-a5ef-eff87edfff8f · outbound

This paper cites Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret

Reference 64

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:57:41.560901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5acc628b-9cd3-4cbe-bdc6-3e9e5550db21 · outbound

This paper cites Intuitively, the duration of this stage is of order O(log T ).

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Intuitively, the duration of this stage is of order O(log T )

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:46.114614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0fb588bb-a554-478a-8a86-8580f921383b · outbound

This paper cites This improved estimation ensures that the condition ∥C L ·,i(t) − C·,i∥∞ ≤ θ continues to hold, thereby guaranteeing the stability of the smallest singular value of C L(t).

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities This improved estimation ensures that the condition ∥C L ·,i(t) − C·,i∥∞ ≤ θ continues to hold, thereby guaranteeing the stability of the smallest singular value of C L(t)

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:45.961864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 76c56b86-e854-4ce4-b798-9483f05d6300 · outbound

This paper cites This stage occurs with a small probability and is expected to last only O(1) rounds.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities This stage occurs with a small probability and is expected to last only O(1) rounds

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:45.748552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3b1f6fa8-6425-49c0-9645-093430bc1093 · outbound

This paper cites an unresolved cited work.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:57:45.586633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1f3172a8-b354-4cb0-b9dc-a94014dec9ec · outbound

This paper cites Based on Lemma 1, the first part of Assumption 2 is satisfied with high probability.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Based on Lemma 1, the first part of Assumption 2 is satisfied with high probability

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:45.484076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a6691b25-2b06-41a4-b12a-248491119a0b · outbound

This paper cites In this case, we upper bound the gap between the expected resource consumption and the average remaining resource as shown in (98).

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities In this case, we upper bound the gap between the expected resource consumption and the average remaining resource as shown in (98)

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:45.338675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 766c46f6-b4be-4339-b860-3523ef38ff3e · outbound

This paper cites Since the resource consumption matrix is element-wise bounded in [0 , 1], we have 0 ≤ E C·,it+1 (b(t))|Ht ≤ 1.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Since the resource consumption matrix is element-wise bounded in [0 , 1], we have 0 ≤ E C·,it+1 (b(t))|Ht ≤ 1

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:45.189854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 31718aff-2803-4003-a40e-cb5a74820ffa · outbound

This paper cites an unresolved cited work.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Unresolved cited work

Reference 72

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:57:45.002491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 137332ab-70ac-49e0-bdfa-665ec068d344 · outbound

This paper cites an unresolved cited work.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Unresolved cited work

Reference 73

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:57:44.845264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fb860a35-094a-4e66-858d-928cb21ebc25 · outbound

This paper cites an unresolved cited work.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Unresolved cited work

Reference 74

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:57:44.756575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6d10d9ad-8785-41ae-b1d5-5fa6b1b3d5f1 · outbound

This paper cites an unresolved cited work.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Unresolved cited work

Reference 75

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:57:44.667277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cf2b2868-4040-42db-82b3-740796dcd93b · outbound

This paper cites For the first summation in (108), it is bound by sX k=1 E[∆k|Hk−1] ≤ TX k=1 |E[∆k|Hk−1]| = αTX k=1 ¯ϵ T − k + T −1X k=αT +1 ϵk T − k ≤ α¯ϵ 1 − α + T −1X k=αT +1 ϵk T − k.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities For the first summation in (108), it is bound by sX k=1 E[∆k|Hk−1] ≤ TX k=1 |E[∆k|Hk−1]| = αTX k=1 ¯ϵ T − k + T −1X k=αT +1 ϵk T − k ≤ α¯ϵ 1 − α + T −1X k=αT +1 ϵk T − k

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:44.550906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers