@article{DBLP:journals/corr/abs-2103-16007,
  author       = {Doris Xin and
                  Hui Miao and
                  Aditya G. Parameswaran and
                  Neoklis Polyzotis},
  title        = {Production Machine Learning Pipelines: Empirical Analysis and Optimization
                  Opportunities},
  journal      = {CoRR},
  volume       = {abs/2103.16007},
  year         = {2021},
  url          = {https://arxiv.org/abs/2103.16007},
  eprinttype    = {arXiv},
  eprint       = {2103.16007},
  timestamp    = {Wed, 07 Apr 2021 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2103-16007.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

{"_id":"Yyt3covr8y9fy9FFv","bibbaseid":"xin-miao-parameswaran-polyzotis-productionmachinelearningpipelinesempiricalanalysisandoptimizationopportunities-2021","author_short":["Xin, D.","Miao, H.","Parameswaran, A. G.","Polyzotis, N."],"bibdata":{"bibtype":"article","type":"article","author":[{"firstnames":["Doris"],"propositions":[],"lastnames":["Xin"],"suffixes":[]},{"firstnames":["Hui"],"propositions":[],"lastnames":["Miao"],"suffixes":[]},{"firstnames":["Aditya","G."],"propositions":[],"lastnames":["Parameswaran"],"suffixes":[]},{"firstnames":["Neoklis"],"propositions":[],"lastnames":["Polyzotis"],"suffixes":[]}],"title":"Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities","journal":"CoRR","volume":"abs/2103.16007","year":"2021","url":"https://arxiv.org/abs/2103.16007","eprinttype":"arXiv","eprint":"2103.16007","timestamp":"Wed, 07 Apr 2021 01:00:00 +0200","biburl":"https://dblp.org/rec/journals/corr/abs-2103-16007.bib","bibsource":"dblp computer science bibliography, https://dblp.org","bibtex":"@article{DBLP:journals/corr/abs-2103-16007,\n author = {Doris Xin and\n Hui Miao and\n Aditya G. Parameswaran and\n Neoklis Polyzotis},\n title = {Production Machine Learning Pipelines: Empirical Analysis and Optimization\n Opportunities},\n journal = {CoRR},\n volume = {abs/2103.16007},\n year = {2021},\n url = {https://arxiv.org/abs/2103.16007},\n eprinttype = {arXiv},\n eprint = {2103.16007},\n timestamp = {Wed, 07 Apr 2021 01:00:00 +0200},\n biburl = {https://dblp.org/rec/journals/corr/abs-2103-16007.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n","author_short":["Xin, D.","Miao, H.","Parameswaran, A. G.","Polyzotis, N."],"key":"DBLP:journals/corr/abs-2103-16007","id":"DBLP:journals/corr/abs-2103-16007","bibbaseid":"xin-miao-parameswaran-polyzotis-productionmachinelearningpipelinesempiricalanalysisandoptimizationopportunities-2021","role":"author","urls":{"Paper":"https://arxiv.org/abs/2103.16007"},"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://dblp.org/pid/135/0135.bib","dataSources":["fTuicW87N9HwLk8iq","zjtj6xZj5ckN4MDjB"],"keywords":[],"search_terms":["production","machine","learning","pipelines","empirical","analysis","optimization","opportunities","xin","miao","parameswaran","polyzotis"],"title":"Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities","year":2021}