Towards VM Rescheduling Optimization Through Deep Reinforcement Learning | Paper Citation Record

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Towards VM Rescheduling Optimization Through Deep Reinforcement Learning Unresolved cited work

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This paper cites Accessed: 2024-10-05.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning Accessed: 2024-10-05

Reference 5

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This paper cites W., Gani, A., Hamid, S.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning W., Gani, A., Hamid, S

Reference 6

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This paper cites InProceedings of the 61st ACM/IEEE Design Automation Conference (2024), pp.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning InProceedings of the 61st ACM/IEEE Design Automation Conference (2024), pp

Reference 7

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This paper cites InProceed- ings of the AAAI Conference on Artificial Intelligence(2020), vol.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning InProceed- ings of the AAAI Conference on Artificial Intelligence(2020), vol

Reference 9

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This paper cites M.Pattern Recognition and Machine Learning (Information Science and Statistics), 1 ed.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning M.Pattern Recognition and Machine Learning (Information Science and Statistics), 1 ed

Reference 10

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Reference 11

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This paper cites Reinforcement Learning Driven Heuristic Optimization.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning Reinforcement Learning Driven Heuristic Optimization

Reference 12

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This paper cites M., and Du, W.Marlp: Time-series forecasting control for agricultural managed aquifer recharge.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning M., and Du, W.Marlp: Time-series forecasting control for agricultural managed aquifer recharge

Reference 13

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This paper cites G., Jul, E., Limpach, C., Pratt, I., and W arfield, A.Live migration of virtual machines.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning G., Jul, E., Limpach, C., Pratt, I., and W arfield, A.Live migration of virtual machines

Reference 14

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This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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This paper cites InInternational Conference on Learning Representations(2021).

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning InInternational Conference on Learning Representations(2021)

Reference 21

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This paper cites A multi-task selected learning approach for solving 3d flexible bin packing problem.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning A multi-task selected learning approach for solving 3d flexible bin packing problem

Reference 22

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This paper cites Reinforcement learning for variable selection in a branch and bound algorithm.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning Reinforcement learning for variable selection in a branch and bound algorithm

Reference 23

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This paper cites Pytorch: An open source machine learning framework.https://pytorch.org/, 2019.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning Pytorch: An open source machine learning framework.https://pytorch.org/, 2019

Reference 24

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This paper cites Advances in Neural Information Processing Systems 32(2019).

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning Advances in Neural Information Processing Systems 32(2019)

Reference 25

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Towards VM Rescheduling Optimization Through Deep Reinforcement Learning T., Nguyen, T

Reference 27

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This paper cites E., Dion, D., Dorminey, S., Joshi, S., Chen, Y., Russinovich, M., et al.Protean: Vm allocation service at scale.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning E., Dion, D., Dorminey, S., Joshi, S., Chen, Y., Russinovich, M., et al.Protean: Vm allocation service at scale

Reference 28

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This paper cites InProceedings of the AAAI conference on artificial intelligence(2018), vol.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning InProceedings of the AAAI conference on artificial intelligence(2018), vol

Reference 30

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This paper cites InProceedings of the 36th Interna- tional Conference on Machine Learning(2019).

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning InProceedings of the 36th Interna- tional Conference on Machine Learning(2019)

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This paper cites InProceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (Melbourne, Australia, July 2018), I.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning InProceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (Melbourne, Australia, July 2018), I

Reference 33

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Towards VM Rescheduling Optimization Through Deep Reinforcement Learning LoRA: Low-Rank Adaptation of Large Language Models

Reference 34

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This paper cites L., Likitha, V., Suneetha, B., and Vignesh, T.Analysis of ci/cd application in kubernetes architec- ture.Mathematical Statistician and Engineering Applications 71, 4 (Mar.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning L., Likitha, V., Suneetha, B., and Vignesh, T.Analysis of ci/cd application in kubernetes architec- ture.Mathematical Statistician and Engineering Applications 71, 4 (Mar

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Towards VM Rescheduling Optimization Through Deep Reinforcement Learning P., Littman, M

Reference 38

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This paper cites In2022 IEEE 9th International Confer- ence on Data Science and Advanced Analytics (DSAA)(2022), pp.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning In2022 IEEE 9th International Confer- ence on Data Science and Advanced Analytics (DSAA)(2022), pp

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Towards VM Rescheduling Optimization Through Deep Reinforcement Learning Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

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Reference 41

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This paper cites InProceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining(New York, NY, USA, 2018), KDD ’18, Association for Computing Machinery, p.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning InProceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining(New York, NY, USA, 2018), KDD ’18, Association for Computing Machinery, p

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This paper cites InProceedings of the 5th Workshop on Machine Learning and Systems(New York, NY, USA, 2025), EuroMLSys ’25, Association for Computing Machinery.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning InProceedings of the 5th Workshop on Machine Learning and Systems(New York, NY, USA, 2025), EuroMLSys ’25, Association for Computing Machinery

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Reference 44

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This paper cites B., Meng, Z., and Alizadeh, M.Learning scheduling algorithms for data processing clusters.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning B., Meng, Z., and Alizadeh, M.Learning scheduling algorithms for data processing clusters

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Reference 46

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This paper cites F., Uhlig, V., Krieger, O., and Xenidis, J.Virtualization for high-performance computing.SIGOPS Oper.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning F., Uhlig, V., Krieger, O., and Xenidis, J.Virtualization for high-performance computing.SIGOPS Oper

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Towards VM Rescheduling Optimization Through Deep Reinforcement Learning InProceedings of the ACM SIGOPS 28th Symposium on Operating Systems Principles(2021)

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Reference 49

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This paper cites microsoft.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning microsoft

Reference 50

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This paper cites M., and Oliveira, J.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning M., and Oliveira, J

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Towards VM Rescheduling Optimization Through Deep Reinforcement Learning K., Larma, M

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Observation 111910f0-608e-44d3-90c1-5b1f35cdda01 · outbound

This paper cites E., Perescu-Popescu, L., and Mastorakis, N.Multilayer perceptron and neural networks.WSEAS Transactions on Circuits and Systems 8, 7 (2009), 579–588.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning E., Perescu-Popescu, L., and Mastorakis, N.Multilayer perceptron and neural networks.WSEAS Transactions on Circuits and Systems 8, 7 (2009), 579–588

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 331db90b-2b4a-4eca-a020-5fd6092ffc97 · outbound

This paper cites Reinforcement Learning with Sparse Rewards using Guidance from Offline Demonstration.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning Reinforcement Learning with Sparse Rewards using Guidance from Offline Demonstration

Reference 54

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Source-reported events for the cited work

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Observation 4a3c80e6-6d7f-4809-9839-b16a3a39a05a · outbound

This paper cites T.Learn- ing by playing solving sparse reward tasks from scratch.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning T.Learn- ing by playing solving sparse reward tasks from scratch

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:28.953698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3ac4a45f-c774-4413-bbc8-be3256104494 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:25.003180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86df78ad-b094-4307-82f7-dd7996454ae3 · outbound

This paper cites H., Rahmani, A.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning H., Rahmani, A

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:28.840911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 55f2c94d-b2d1-41b0-8475-6cfffd346d5c · outbound

This paper cites an unresolved cited work.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:56:28.698866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c888a472-bcc3-40c5-8b1f-c128364c70e5 · outbound

This paper cites an unresolved cited work.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:56:28.554422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a4a38930-1d1c-4c22-a2f1-d03af1e17745 · outbound

This paper cites A., Yousafzai, A., V asilakos, A.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning A., Yousafzai, A., V asilakos, A

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:28.407718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 731bb7a3-6693-4448-846e-1f1c27b51ebf · outbound

This paper cites InPro- ceedings of the Seventeenth European Conference on Computer Systems (2022), pp.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning InPro- ceedings of the Seventeenth European Conference on Computer Systems (2022), pp

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:28.180037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 415afff2-3371-4c49-8f4e-58fd05b3af7a · outbound

This paper cites N., Kaiser, Ł., and Polosukhin, I.Attention is all you need.Ad- vances in neural information processing systems 30(2017).

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning N., Kaiser, Ł., and Polosukhin, I.Attention is all you need.Ad- vances in neural information processing systems 30(2017)

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:28.047260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 48865da8-af30-41d5-936f-690e31048069 · outbound

This paper cites K., Shenoy, P., V an Der Merwe, J., Hwang, J., Liu, G., and Chaufournier, L.Cloudnet: dynamic pool- ing of cloud resources by live wan migration of virtual machines.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning K., Shenoy, P., V an Der Merwe, J., Hwang, J., Liu, G., and Chaufournier, L.Cloudnet: dynamic pool- ing of cloud resources by live wan migration of virtual machines

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:27.904841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ffbfdc5d-7847-4582-9e2a-c210825216cc · outbound

This paper cites an unresolved cited work.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning Unresolved cited work

Reference 64

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:56:27.667751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5098fa7f-f557-44c6-9360-18665b179437 · outbound

This paper cites InProceedings of the 22nd International Conference on Information Processing in Sensor Networks(2023).

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning InProceedings of the 22nd International Conference on Information Processing in Sensor Networks(2023)

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:27.475718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 377b24b4-d595-4903-9252-0ce72d639bd1 · outbound

This paper cites InACM MobiSys(2024).

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning InACM MobiSys(2024)

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:27.270899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ef3fb5fb-848b-4916-80ea-4849ed437abb · outbound

This paper cites Attend2Pack: Bin Packing through Deep Reinforcement Learning with Attention.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning Attend2Pack: Bin Packing through Deep Reinforcement Learning with Attention

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:26.058900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7732ba3f-7caa-48e5-99fc-d57fa383af26 · outbound

This paper cites an unresolved cited work.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning Unresolved cited work

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:26.171656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f69e38c-d6be-40ae-b444-9e8841c3b6d5 · outbound

This paper cites S., Tian, Y., Zhang, Y., and Jin, X.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning S., Tian, Y., Zhang, Y., and Jin, X

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:27.062527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cee11de8-098a-4456-a175-fe898974ab85 · outbound

This paper cites Learning to pack: A data-driven tree search algorithm for large-scale 3d bin packing problem.

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning Learning to pack: A data-driven tree search algorithm for large-scale 3d bin packing problem

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:26.831194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Outbound references

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