{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T14:20:45Z","timestamp":1770042045858,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":31,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T00:00:00Z","timestamp":1635724800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,11]]},"DOI":"10.1145\/3472883.3486989","type":"proceedings-article","created":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T10:48:16Z","timestamp":1635331696000},"page":"33-46","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Elastic Hyperparameter Tuning on the Cloud"],"prefix":"10.1145","author":[{"given":"Lisa","family":"Dunlap","sequence":"first","affiliation":[{"name":"UC Berkeley"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kirthevasan","family":"Kandasamy","sequence":"additional","affiliation":[{"name":"UC Berkeley"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ujval","family":"Misra","sequence":"additional","affiliation":[{"name":"UC Berkeley"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Richard","family":"Liaw","sequence":"additional","affiliation":[{"name":"UC Berkeley"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Jordan","sequence":"additional","affiliation":[{"name":"UC Berkeley"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ion","family":"Stoica","sequence":"additional","affiliation":[{"name":"UC Berkeley"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joseph E.","family":"Gonzalez","sequence":"additional","affiliation":[{"name":"UC Berkeley"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,11]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Andrew Gordon Wilson, and Eytan Bakshy","author":"Balandat Maximilian","year":"2019","unstructured":"Maximilian Balandat , Brian Karrer , Daniel R Jiang , Samuel Daulton , Benjamin Letham , Andrew Gordon Wilson, and Eytan Bakshy . 2019 . Botorch : Programmable bayesian optimization in pytorch. arXiv preprint arXiv:1910.06403 (2019). Maximilian Balandat, Brian Karrer, Daniel R Jiang, Samuel Daulton, Benjamin Letham, Andrew Gordon Wilson, and Eytan Bakshy. 2019. Botorch: Programmable bayesian optimization in pytorch. arXiv preprint arXiv:1910.06403 (2019)."},{"key":"e_1_3_2_2_2_1","unstructured":"James S. Bergstra R\u00e9mi Bardenet Yoshua Bengio and Bal\u00e1zs K\u00e9gl. 2011. Algorithms for Hyper-Parameter Optimization. In Advances in Neural Information Processing Systems.  James S. Bergstra R\u00e9mi Bardenet Yoshua Bengio and Bal\u00e1zs K\u00e9gl. 2011. Algorithms for Hyper-Parameter Optimization. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1561\/9781601986276"},{"key":"e_1_3_2_2_4_1","volume-title":"Conference on Learning Theory. 590--604","author":"Carpentier Alexandra","year":"2016","unstructured":"Alexandra Carpentier and Andrea Locatelli . 2016 . Tight (lower) bounds for the fixed budget best arm identification bandit problem . In Conference on Learning Theory. 590--604 . Alexandra Carpentier and Andrea Locatelli. 2016. Tight (lower) bounds for the fixed budget best arm identification bandit problem. In Conference on Learning Theory. 590--604."},{"key":"e_1_3_2_2_5_1","volume-title":"Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin , Ming-Wei Chang , Kenton Lee , and Kristina Toutanova . 2018 . Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018). Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"e_1_3_2_2_7_1","volume-title":"BOHB: Robust and Efficient Hyperparameter Optimization at Scale. CoRR abs\/1807.01774","author":"Falkner Stefan","year":"2018","unstructured":"Stefan Falkner , Aaron Klein , and Frank Hutter . 2018 . BOHB: Robust and Efficient Hyperparameter Optimization at Scale. CoRR abs\/1807.01774 (2018). arXiv:1807.01774 http:\/\/arxiv.org\/abs\/1807.01774 Stefan Falkner, Aaron Klein, and Frank Hutter. 2018. BOHB: Robust and Efficient Hyperparameter Optimization at Scale. CoRR abs\/1807.01774 (2018). arXiv:1807.01774 http:\/\/arxiv.org\/abs\/1807.01774"},{"key":"e_1_3_2_2_8_1","unstructured":"Matthias Feurer A. Klein K. Eggensperger J. Springenberg M. Blum and F. Hutter. 2015. Efficient and robust automated machine learning. Advances in Neural Information Processing Systems 28 (01 2015) 2944--2952.  Matthias Feurer A. Klein K. Eggensperger J. Springenberg M. Blum and F. Hutter. 2015. Efficient and robust automated machine learning. Advances in Neural Information Processing Systems 28 (01 2015) 2944--2952."},{"key":"e_1_3_2_2_9_1","volume-title":"Yuan Tang, Ramdoot Pydipaty, and Amit Kumar Saha.","author":"George Johnu","year":"2020","unstructured":"Johnu George , Ce Gao , Richard Liu , Hou Gang Liu , Yuan Tang, Ramdoot Pydipaty, and Amit Kumar Saha. 2020 . A Scalable and Cloud-Native Hyperparameter Tuning System . arXiv:2006.02085 [cs.DC] Johnu George, Ce Gao, Richard Liu, Hou Gang Liu, Yuan Tang, Ramdoot Pydipaty, and Amit Kumar Saha. 2020. A Scalable and Cloud-Native Hyperparameter Tuning System. arXiv:2006.02085 [cs.DC]"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098043"},{"key":"e_1_3_2_2_11_1","volume-title":"Deep Residual Learning for Image Recognition. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"He Kaiming","year":"2016","unstructured":"Kaiming He , Xiangyu Zhang , Shaoqing Ren , and Jian Sun . 2016 . Deep Residual Learning for Image Recognition. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep Residual Learning for Image Recognition. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"crossref","unstructured":"Frank Hutter Holger H. Hoos and Kevin Leyton-Brown. 2011. Sequential Model-based Optimization for General Algorithm Configuration. In LION.  Frank Hutter Holger H. Hoos and Kevin Leyton-Brown. 2011. Sequential Model-based Optimization for General Algorithm Configuration. In LION.","DOI":"10.1007\/978-3-642-25566-3_40"},{"key":"e_1_3_2_2_13_1","volume-title":"Elastic Resource Sharing for Distributed Deep Learning. In USENIX Symposium on Network Design and Implementation (NDSI 21)","author":"Hwang Changho","year":"2021","unstructured":"Changho Hwang , Taehyun Kim , Sunghyun Kim , Jinwoo Shin , and KyoungSoo Park . 2021 . Elastic Resource Sharing for Distributed Deep Learning. In USENIX Symposium on Network Design and Implementation (NDSI 21) . USENIX Association. Changho Hwang, Taehyun Kim, Sunghyun Kim, Jinwoo Shin, and KyoungSoo Park. 2021. Elastic Resource Sharing for Distributed Deep Learning. In USENIX Symposium on Network Design and Implementation (NDSI 21). USENIX Association."},{"key":"e_1_3_2_2_14_1","unstructured":"Kevin Jamieson and Ameet Talwalkar. 2016. Non-stochastic best arm identification and hyperparameter optimization. In Artificial Intelligence and Statistics. 240--248.  Kevin Jamieson and Ameet Talwalkar. 2016. Non-stochastic best arm identification and hyperparameter optimization. In Artificial Intelligence and Statistics. 240--248."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"crossref","unstructured":"D. R. Jones C. D. Perttunen and B. E. Stuckman. 1993. Lipschitzian Optimization Without the Lipschitz Constant. J. Optim. Theory Appl. (1993).  D. R. Jones C. D. Perttunen and B. E. Stuckman. 1993. Lipschitzian Optimization Without the Lipschitz Constant. J. Optim. Theory Appl. (1993).","DOI":"10.1007\/BF00941892"},{"key":"e_1_3_2_2_16_1","first-page":"1","article-title":"Tuning hyperparameters without grad students: Scalable and robust bayesian optimisation with dragonfly","volume":"21","author":"Kandasamy Kirthevasan","year":"2020","unstructured":"Kirthevasan Kandasamy , Karun Raju Vysyaraju , Willie Neiswanger , Biswajit Paria , Christopher R Collins , Jeff Schneider , Barnabas Poczos , and Eric P Xing . 2020 . Tuning hyperparameters without grad students: Scalable and robust bayesian optimisation with dragonfly . Journal of Machine Learning Research 21 , 81 (2020), 1 -- 27 . Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger, Biswajit Paria, Christopher R Collins, Jeff Schneider, Barnabas Poczos, and Eric P Xing. 2020. Tuning hyperparameters without grad students: Scalable and robust bayesian optimisation with dragonfly. Journal of Machine Learning Research 21, 81 (2020), 1--27.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_2_17_1","volume-title":"International Conference on Machine Learning. 1238--1246","author":"Karnin Zohar","year":"2013","unstructured":"Zohar Karnin , Tomer Koren , and Oren Somekh . 2013 . Almost optimal exploration in multi-armed bandits . In International Conference on Machine Learning. 1238--1246 . Zohar Karnin, Tomer Koren, and Oren Somekh. 2013. Almost optimal exploration in multi-armed bandits. In International Conference on Machine Learning. 1238--1246."},{"key":"e_1_3_2_2_19_1","unstructured":"Ya Le and Xuan Yang. 2015. Tiny ImageNet Visual Recognition Challenge.  Ya Le and Xuan Yang. 2015. Tiny ImageNet Visual Recognition Challenge."},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.5555\/3122009.3242042"},{"key":"e_1_3_2_2_21_1","volume-title":"Proceedings of Workshop on ML Systems in The Thirty-second Annual Conference on Neural Information Processing Systems (NIPS).","author":"Li Liam","year":"2018","unstructured":"Liam Li , Kevin Jamieson , Afshin Rostamizadeh , Ekaterina Gonina , Moritz Hardt , Benjamin Recht , and Ameet Talwalkar . 2018 . Massively Parallel Hyperparameter Tuning . In Proceedings of Workshop on ML Systems in The Thirty-second Annual Conference on Neural Information Processing Systems (NIPS). Liam Li, Kevin Jamieson, Afshin Rostamizadeh, Ekaterina Gonina, Moritz Hardt, Benjamin Recht, and Ameet Talwalkar. 2018. Massively Parallel Hyperparameter Tuning. In Proceedings of Workshop on ML Systems in The Thirty-second Annual Conference on Neural Information Processing Systems (NIPS)."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357223.3362719"},{"key":"e_1_3_2_2_23_1","volume-title":"Tune: A Research Platform for Distributed Model Selection and Training. arXiv preprint arXiv:1807.05118","author":"Liaw Richard","year":"2018","unstructured":"Richard Liaw , Eric Liang , Robert Nishihara , Philipp Moritz , Joseph E Gonzalez , and Ion Stoica . 2018 . Tune: A Research Platform for Distributed Model Selection and Training. arXiv preprint arXiv:1807.05118 (2018). Richard Liaw, Eric Liang, Robert Nishihara, Philipp Moritz, Joseph E Gonzalez, and Ion Stoica. 2018. Tune: A Research Platform for Distributed Model Selection and Training. arXiv preprint arXiv:1807.05118 (2018)."},{"key":"e_1_3_2_2_24_1","volume-title":"Rubberband: Cloud Based Hyperparameter Tuning. EuroSys","author":"Liaw Richard","year":"2021","unstructured":"Richard Liaw , Ujval Misra , Lisa Dunlap , Romil Bhardwaj , Alexey Tumanov , Joey E. Gonzalez , and Ion Stoica . 2021 . Rubberband: Cloud Based Hyperparameter Tuning. EuroSys (2021). Richard Liaw, Ujval Misra, Lisa Dunlap, Romil Bhardwaj, Alexey Tumanov, Joey E. Gonzalez, and Ion Stoica. 2021. Rubberband: Cloud Based Hyperparameter Tuning. EuroSys (2021)."},{"key":"e_1_3_2_2_25_1","volume-title":"Ray: A distributed framework for emerging {AI} applications. In 13th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 18). 561--577.","author":"Moritz Philipp","year":"2018","unstructured":"Philipp Moritz , Robert Nishihara , Stephanie Wang , Alexey Tumanov , Richard Liaw , Eric Liang , Melih Elibol , Zongheng Yang , William Paul , Michael I Jordan , 2018 . Ray: A distributed framework for emerging {AI} applications. In 13th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 18). 561--577. Philipp Moritz, Robert Nishihara, Stephanie Wang, Alexey Tumanov, Richard Liaw, Eric Liang, Melih Elibol, Zongheng Yang, William Paul, Michael I Jordan, et al. 2018. Ray: A distributed framework for emerging {AI} applications. In 13th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 18). 561--577."},{"key":"e_1_3_2_2_26_1","volume-title":"Reading Digits in Natural Images with Unsupervised Feature Learning. In NIPS Workshop on Deep Learning and Unsupervised Feature Learning.","author":"Netzer Yuval","unstructured":"Yuval Netzer , Tao Wang , Adam Coates , Alessandro Bissacco , Bo Wu , and Andrew Y. Ng . 2011 . Reading Digits in Natural Images with Unsupervised Feature Learning. In NIPS Workshop on Deep Learning and Unsupervised Feature Learning. Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, and Andrew Y. Ng. 2011. Reading Digits in Natural Images with Unsupervised Feature Learning. In NIPS Workshop on Deep Learning and Unsupervised Feature Learning."},{"key":"e_1_3_2_2_27_1","volume-title":"Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning. In 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21)","author":"Qiao Aurick","unstructured":"Aurick Qiao , Sang Keun Choe , Suhas Jayaram Subramanya , Willie Neiswanger , Qirong Ho , Hao Zhang , Gregory R. Ganger , and Eric P. Xing . 2021 . Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning. In 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21) . USENIX Association, 1--18. https:\/\/www.usenix.org\/conference\/osdi21\/presentation\/qiao Aurick Qiao, Sang Keun Choe, Suhas Jayaram Subramanya, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R. Ganger, and Eric P. Xing. 2021. Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning. In 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21). USENIX Association, 1--18. https:\/\/www.usenix.org\/conference\/osdi21\/presentation\/qiao"},{"key":"e_1_3_2_2_28_1","volume-title":"Improving Fully Convolution Network for Semantic Segmentation. CoRR abs\/1611.08986","author":"Shuai Bing","year":"2016","unstructured":"Bing Shuai , Ting Liu , and Gang Wang . 2016. Improving Fully Convolution Network for Semantic Segmentation. CoRR abs\/1611.08986 ( 2016 ). arXiv:1611.08986 http:\/\/arxiv.org\/abs\/1611.08986 Bing Shuai, Ting Liu, and Gang Wang. 2016. Improving Fully Convolution Network for Semantic Segmentation. CoRR abs\/1611.08986 (2016). arXiv:1611.08986 http:\/\/arxiv.org\/abs\/1611.08986"},{"key":"e_1_3_2_2_29_1","unstructured":"Karen Simonyan and Andrew Zisserman. 2014. Very Deep Convolutional Networks for Large-Scale Image Recognition.  Karen Simonyan and Andrew Zisserman. 2014. Very Deep Convolutional Networks for Large-Scale Image Recognition."},{"key":"e_1_3_2_2_30_1","unstructured":"Jasper Snoek Hugo Larochelle and Ryan P Adams. 2012. Practical Bayesian Optimization of Machine Learning Algorithms. In Advances in Neural Information Processing Systems.  Jasper Snoek Hugo Larochelle and Ryan P Adams. 2012. Practical Bayesian Optimization of Machine Learning Algorithms. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_2_31_1","volume-title":"Bowman","author":"Wang Alex","year":"2018","unstructured":"Alex Wang , Amanpreet Singh , Julian Michael , Felix Hill , Omer Levy , and Samuel R . Bowman . 2018 . GLUE : A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding . (2018). arXiv preprint 1804.07461. Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 2018. GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding. (2018). arXiv preprint 1804.07461."},{"key":"e_1_3_2_2_32_1","volume-title":"HuggingFace's Transformers: State-of-the-art Natural Language Processing. CoRR abs\/1910.03771","author":"Wolf Thomas","year":"2019","unstructured":"Thomas Wolf , Lysandre Debut , Victor Sanh , Julien Chaumond , Clement Delangue , Anthony Moi , Pierric Cistac , Tim Rault , R\u00e9mi Louf , Morgan Funtowicz , and Jamie Brew . 2019. HuggingFace's Transformers: State-of-the-art Natural Language Processing. CoRR abs\/1910.03771 ( 2019 ). arXiv:1910.03771 http:\/\/arxiv.org\/abs\/1910.03771 Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, R\u00e9mi Louf, Morgan Funtowicz, and Jamie Brew. 2019. HuggingFace's Transformers: State-of-the-art Natural Language Processing. CoRR abs\/1910.03771 (2019). arXiv:1910.03771 http:\/\/arxiv.org\/abs\/1910.03771"}],"event":{"name":"SoCC '21: ACM Symposium on Cloud Computing","location":"Seattle WA USA","acronym":"SoCC '21","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGOPS ACM Special Interest Group on Operating Systems"]},"container-title":["Proceedings of the ACM Symposium on Cloud Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3472883.3486989","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3472883.3486989","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:11:57Z","timestamp":1750191117000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3472883.3486989"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11]]},"references-count":31,"alternative-id":["10.1145\/3472883.3486989","10.1145\/3472883"],"URL":"https:\/\/doi.org\/10.1145\/3472883.3486989","relation":{},"subject":[],"published":{"date-parts":[[2021,11]]},"assertion":[{"value":"2021-11-01","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}