{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T14:54:43Z","timestamp":1788879283477,"version":"build-2803163510"},"publisher-location":"New York, NY, USA","reference-count":47,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,3,30]],"date-time":"2025-03-30T00:00:00Z","timestamp":1743292800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,3,30]]},"DOI":"10.1145\/3689031.3696065","type":"proceedings-article","created":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T06:25:20Z","timestamp":1742970320000},"page":"413-427","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["Achieving Fairness Generalizability for Learning-based Congestion Control with Jury"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3238-8500","authenticated-orcid":false,"given":"Han","family":"Tian","sequence":"first","affiliation":[{"name":"University of Science and Technology of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8380-1879","authenticated-orcid":false,"given":"Xudong","family":"Liao","sequence":"additional","affiliation":[{"name":"iSING Lab, Hong Kong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3442-4656","authenticated-orcid":false,"given":"Decang","family":"Sun","sequence":"additional","affiliation":[{"name":"iSING Lab, Hong Kong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5151-0997","authenticated-orcid":false,"given":"Chaoliang","family":"Zeng","sequence":"additional","affiliation":[{"name":"BitIntelligence"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9502-7622","authenticated-orcid":false,"given":"Yilun","family":"Jin","sequence":"additional","affiliation":[{"name":"iSING Lab, Hong Kong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6926-7801","authenticated-orcid":false,"given":"Junxue","family":"Zhang","sequence":"additional","affiliation":[{"name":"iSING Lab, Hong Kong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6503-5309","authenticated-orcid":false,"given":"Xinchen","family":"Wan","sequence":"additional","affiliation":[{"name":"iSING Lab, Hong Kong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3184-4081","authenticated-orcid":false,"given":"Zilong","family":"Wang","sequence":"additional","affiliation":[{"name":"iSING Lab, Hong Kong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8699-8355","authenticated-orcid":false,"given":"Yong","family":"Wang","sequence":"additional","affiliation":[{"name":"iSING Lab, Hong Kong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2587-6028","authenticated-orcid":false,"given":"Kai","family":"Chen","sequence":"additional","affiliation":[{"name":"iSING Lab, Hong Kong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,3,30]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3387514.3405892"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3232755.3232783"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Lawrence S Brakmo Sean W O'Malley and Larry L Peterson. 1994. TCP Vegas: New techniques for congestion detection and avoidance. Number 4. ACM.","DOI":"10.1145\/190809.190317"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3012426.3022184"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2619239.2626315"},{"key":"e_1_3_2_1_6_1","volume-title":"International Conference on Machine Learning. PMLR, 1282--1289","author":"Cobbe Karl","year":"2019","unstructured":"Karl Cobbe, Oleg Klimov, Chris Hesse, Taehoon Kim, and John Schulman. 2019. Quantifying generalization in reinforcement learning. In International Conference on Machine Learning. PMLR, 1282--1289."},{"key":"e_1_3_2_1_7_1","volume-title":"PCC: Re-architecting Congestion Control for Consistent High Performance. In 12th USENIX Symposium on Networked Systems Design and Implementation (NSDI 15)","author":"Dong Mo","year":"2015","unstructured":"Mo Dong, Qingxi Li, Doron Zarchy, P Brighten Godfrey, and Michael Schapira. 2015. PCC: Re-architecting Congestion Control for Consistent High Performance. In 12th USENIX Symposium on Networked Systems Design and Implementation (NSDI 15). 395--408."},{"key":"e_1_3_2_1_8_1","volume-title":"PCC Vivace: Online-Learning Congestion Control. In 15th USENIX Symposium on Networked Systems Design and Implementation (NSDI 18)","author":"Dong Mo","year":"2018","unstructured":"Mo Dong, Tong Meng, Doron Zarchy, Engin Arslan, Yossi Gilad, Brighten Godfrey, and Michael Schapira. 2018. PCC Vivace: Online-Learning Congestion Control. In 15th USENIX Symposium on Networked Systems Design and Implementation (NSDI 18). USENIX Association, Renton, WA, 343--356."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485983.3494840"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2022.3185253"},{"key":"e_1_3_2_1_11_1","unstructured":"DI engine Contributors. 2021. DI-engine: OpenDILab Decision Intelligence Engine. https:\/\/github.com\/opendilab\/DI-engine."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/1536414.1536486"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"crossref","unstructured":"Sally Floyd Tom Henderson Andrei Gurtov et al. 1999. The NewReno modification to TCP's fast recovery algorithm. (1999).","DOI":"10.17487\/rfc2582"},{"key":"e_1_3_2_1_14_1","volume-title":"International Conference on Machine Learning. PMLR, 1587--1596","author":"Fujimoto Scott","year":"2018","unstructured":"Scott Fujimoto, Herke Hoof, and David Meger. 2018. Addressing function approximation error in actor-critic methods. In International Conference on Machine Learning. PMLR, 1587--1596."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1400097.1400105"},{"key":"e_1_3_2_1_16_1","volume-title":"14th USENIX Symposium on Operating Systems Design and Implementation (OSDI 20)","author":"Hao Mingzhe","year":"2020","unstructured":"Mingzhe Hao, Levent Toksoz, Nanqinqin Li, Edward Edberg Halim, Henry Hoffmann, and Haryadi S Gunawi. 2020. {LinnOS}: Predictability on Unpredictable Flash Storage with a Light Neural Network. In 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI 20). 173--190."},{"key":"e_1_3_2_1_17_1","volume-title":"Congestion avoidance and control. ACM SIGCOMM computer communication review 18, 4","author":"Jacobson Van","year":"1988","unstructured":"Van Jacobson. 1988. Congestion avoidance and control. ACM SIGCOMM computer communication review 18, 4 (1988), 314--329."},{"key":"e_1_3_2_1_18_1","volume-title":"International Conference on Machine Learning ICML. 3050--3059","author":"Jay Nathan","year":"2019","unstructured":"Nathan Jay, Noga Rotman, Brighten Godfrey, Michael Schapira, and Aviv Tamar. 2019. A Deep Reinforcement Learning Perspective on Internet Congestion Control. In International Conference on Machine Learning ICML. 3050--3059."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2021.108033"},{"key":"e_1_3_2_1_20_1","volume-title":"A survey of generalisation in deep reinforcement learning. arXiv preprint arXiv:2111.09794","author":"Kirk Robert","year":"2021","unstructured":"Robert Kirk, Amy Zhang, Edward Grefenstette, and Tim Rockt\u00e4schel. 2021. A survey of generalisation in deep reinforcement learning. arXiv preprint arXiv:2111.09794 (2021)."},{"key":"e_1_3_2_1_21_1","volume-title":"A survey of generalisation in deep reinforcement learning. arXiv preprint arXiv:2111.09794","author":"Kirk Robert","year":"2021","unstructured":"Robert Kirk, Amy Zhang, Edward Grefenstette, and Tim Rockt\u00e4schel. 2021. A survey of generalisation in deep reinforcement learning. arXiv preprint arXiv:2111.09794 (2021)."},{"key":"e_1_3_2_1_22_1","volume-title":"Deep learning. nature 521, 7553","author":"LeCun Yann","year":"2015","unstructured":"Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. nature 521, 7553 (2015), 436--444."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3627703.3650069"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3492321.3519593"},{"key":"e_1_3_2_1_25_1","first-page":"8032","article-title":"When Is Generalizable Reinforcement Learning Tractable","volume":"34","author":"Malik Dhruv","year":"2021","unstructured":"Dhruv Malik, Yuanzhi Li, and Pradeep Ravikumar. 2021. When Is Generalizable Reinforcement Learning Tractable? Advances in Neural Information Processing Systems 34 (2021), 8032--8045.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3098822.3098843"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3341302.3342080"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3387514.3405891"},{"key":"e_1_3_2_1_29_1","volume-title":"International conference on machine learning. PMLR","author":"Mnih Volodymyr","year":"2016","unstructured":"Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu. 2016. Asynchronous methods for deep reinforcement learning. In International conference on machine learning. PMLR, 1928--1937."},{"key":"e_1_3_2_1_30_1","volume-title":"Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602","author":"Mnih Volodymyr","year":"2013","unstructured":"Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller. 2013. Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602 (2013)."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"crossref","unstructured":"Volodymyr Mnih Koray Kavukcuoglu David Silver Andrei A Rusu Joel Veness Marc G Bellemare Alex Graves Martin Riedmiller Andreas K Fidjeland Georg Ostrovski et al. 2015. Human-level control through deep reinforcement learning nature 518 7540 (2015) 529--533.","DOI":"10.1038\/nature14236"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/2740070.2631455"},{"key":"e_1_3_2_1_33_1","volume-title":"Gotta learn fast: A new benchmark for generalization in rl. arXiv preprint arXiv:1804.03720","author":"Nichol Alex","year":"2018","unstructured":"Alex Nichol, Vicki Pfau, Christopher Hesse, Oleg Klimov, and John Schulman. 2018. Gotta learn fast: A new benchmark for generalization in rl. arXiv preprint arXiv:1804.03720 (2018)."},{"key":"e_1_3_2_1_34_1","volume-title":"PyTorch: An Imperative Style","author":"Paszke Adam","unstructured":"Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019. PyTorch: An Imperative Style, High-Performance Deep Learning Library. In Advances in Neural Information Processing Systems 32, H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alch\u00e9-Buc, E. Fox, and R. Garnett (Eds.). Curran Associates, Inc., 8024--8035. http:\/\/papers.neurips.cc\/paper\/9015-pytorch-an-imperative-style-high-performance-deep-learning-library.pdf"},{"key":"e_1_3_2_1_35_1","volume-title":"Automatic data augmentation for generalization in deep reinforcement learning. arXiv preprint arXiv:2006.12862","author":"Raileanu Roberta","year":"2020","unstructured":"Roberta Raileanu, Max Goldstein, Denis Yarats, Ilya Kostrikov, and Rob Fergus. 2020. Automatic data augmentation for generalization in deep reinforcement learning. arXiv preprint arXiv:2006.12862 (2020)."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM42981.2021.9488851"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"crossref","unstructured":"J Salim H Khosravi Andi Kleen and Alexey Kuznetsov. 2003. Linux netlink as an ip services protocol. Technical Report.","DOI":"10.17487\/rfc3549"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"crossref","unstructured":"David Silver Thomas Hubert Julian Schrittwieser Ioannis Antonoglou Matthew Lai Arthur Guez Marc Lanctot Laurent Sifre Dharshan Kumaran Thore Graepel et al. 2018. A general reinforcement learning algorithm that masters chess shogi and Go through self-play. Science 362 6419 (2018) 1140--1144.","DOI":"10.1126\/science.aar6404"},{"key":"e_1_3_2_1_39_1","unstructured":"Open Ended Learning Team Adam Stooke Anuj Mahajan Catarina Barros Charlie Deck Jakob Bauer Jakub Sygnowski Maja Trebacz Max Jaderberg Michael Mathieu et al. 2021. Open-ended learning leads to generally capable agents. arXiv preprint arXiv:2107.12808 (2021)."},{"key":"e_1_3_2_1_40_1","unstructured":"The Google BBR Team. [n. d.]. BBR bandwidth based convergence. https:\/\/github.com\/google\/bbr\/blob\/master\/Documentation\/bbr_bandwidth_based_convergence.pdf."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3555050.3569125"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2012.6386109"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/2486001.2486020"},{"key":"e_1_3_2_1_44_1","volume-title":"10th USENIX Symposium on Networked Systems Design and Implementation (NSDI 13)","author":"Winstein Keith","year":"2013","unstructured":"Keith Winstein, Anirudh Sivaraman, and Hari Balakrishnan. 2013. Stochastic forecasts achieve high throughput and low delay over cellular networks. In 10th USENIX Symposium on Networked Systems Design and Implementation (NSDI 13). 459--471."},{"key":"e_1_3_2_1_45_1","volume-title":"2018 USENIX Annual Technical Conference (USENIX ATC 18)","author":"Yan Francis Y","year":"2018","unstructured":"Francis Y Yan, Jestin Ma, Greg D Hill, Deepti Raghavan, Riad S Wahby, Philip Levis, and Keith Winstein. 2018. Pantheon: the training ground for Internet congestion-control research. In 2018 USENIX Annual Technical Conference (USENIX ATC 18)."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/3452296.3472927"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3544216.3544229"}],"event":{"name":"EuroSys '25: Twentieth European Conference on Computer Systems","location":"Rotterdam Netherlands","acronym":"EuroSys '25","sponsor":["SIGOPS ACM Special Interest Group on Operating Systems"]},"container-title":["Proceedings of the Twentieth European Conference on Computer Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3689031.3696065","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3689031.3696065","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T11:24:56Z","timestamp":1755775496000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3689031.3696065"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,30]]},"references-count":47,"alternative-id":["10.1145\/3689031.3696065","10.1145\/3689031"],"URL":"https:\/\/doi.org\/10.1145\/3689031.3696065","relation":{},"subject":[],"published":{"date-parts":[[2025,3,30]]},"assertion":[{"value":"2025-03-30","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}