Machine learning could improve innovation policy

被引:0
|
作者
Jeffrey L. Furman
Florenta Teodoridis
机构
[1] Boston University,
[2] National Bureau of Economic Research,undefined
[3] University of Southern California,undefined
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
页码:84 / 84
相关论文
共 50 条
  • [21] Poor enforcement could jeopardize China's drug innovation policy
    Hepeng Jia
    [J]. Nature Biotechnology, 2006, 24 : 1182 - 1183
  • [22] Policy learning and the 'cluster-flavoured innovation policy' in Finland
    Sotarauta, Markku
    [J]. ENVIRONMENT AND PLANNING C-GOVERNMENT AND POLICY, 2012, 30 (05): : 780 - 795
  • [23] Could Machine Learning Break the Convection Parameterization Deadlock?
    Gentine, P.
    Pritchard, M.
    Rasp, S.
    Reinaudi, G.
    Yacalis, G.
    [J]. GEOPHYSICAL RESEARCH LETTERS, 2018, 45 (11) : 5742 - 5751
  • [24] Probabilistic Machine Learning Could Eliminate No Fault Found
    Teixeira, Rodrigo E.
    Morris, Kari E.
    Sautter, F. Christian
    [J]. PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON THROUGH-LIFE ENGINEERING SERVICES, 2015, 38 : 124 - 128
  • [25] Could machine learning fuel a reproducibility crisis in science?
    Elizabeth Gibney
    [J]. Nature, 2022, 608 : 250 - 251
  • [26] Machine learning for continuous innovation in battery technologies
    Muratahan Aykol
    Patrick Herring
    Abraham Anapolsky
    [J]. Nature Reviews Materials, 2020, 5 : 725 - 727
  • [27] Balancing innovation and privacy : A machine learning perspective
    Upadhyay, Utsav
    Kumar, Alok
    Roy, Satyabrata
    Rawat, Umashankar
    [J]. JOURNAL OF DISCRETE MATHEMATICAL SCIENCES & CRYPTOGRAPHY, 2024, 27 (2B): : 547 - 557
  • [28] Flashlight: Enabling Innovation in Tools for Machine Learning
    Kahn, Jacob
    Pratap, Vineel
    Likhomanenko, Tatiana
    Xu, Qiantong
    Hannun, Awni
    Cai, Jeff
    Tomasello, Paden
    Lee, Ann
    Grave, Edouard
    Avidov, Gilad
    Steiner, Benoit
    Liptchinsky, Vitaliy
    Synnaeve, Gabriel
    Collobert, Ronan
    [J]. INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 162, 2022, : 10557 - 10574
  • [29] Moving machine learning from innovation to production
    de Morsier Picterra, Frank
    [J]. GIM INTERNATIONAL-THE WORLDWIDE MAGAZINE FOR GEOMATICS, 2024, 38 (02):
  • [30] Leveraging machine learning in the innovation of functional materials
    Sun, Zhehao
    Yin, Hang
    Yin, Zongyou
    [J]. MATTER, 2023, 6 (08) : 2553 - 2555