Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Flora Haberkorn"'
Autor:
Aaron Flaaen, Rosemary Rhodes, Anderson Monken, Justin R. Pierce, Logan T. Lewis, Flora Haberkorn, Madeleine Yi
Publikováno v:
Review of International Economics.
We evaluate high-frequency bill of lading data for its suitability in international trade research. These data offer many advantages over both other publicly accessible official trade data and confidential datasets, but they also have clear drawbacks
Autor:
Farid Ahmed, Ayodeji Alajo, Syed Bahauddin Alam, Amira Al-Khulaidy Stine, William Ampeh, Ashita Anuga, Feras A. Batarseh, Sindhu Bharathi, Sumathi Chakravarthy, Jaganmohan Chandrasekaran, Laura J. Freeman, Jay Gendron, Nitish Gorentala, Sai Gurrapu, Flora Haberkorn, Hamdi Kavak, Uma Krishnaswamy, Erik W. Kuiler, Dinesh Kumar, William Franz Lamberti, Antoni Lorente, Ralitsa Maduro, Connie L. McNeely, Anderson Monken, Badri Narayanan, Shounkie Nawani, Minh Nguyen, Kim Niewolny, Ayorinde Ogunyiola, Dominick J. Perini, Brianna B. Posadas, Abdul Rahman, Md Nazmul Kabir Sikder, Andrei Svetovidov, Amanda Tolman, Hong-Linh Truong, Shoaib Usman, Pei Wang, Madison J. Williams
Publikováno v:
AI Assurance ISBN: 9780323919197
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7f70d2123e3ff14af788ea8804f25704
https://doi.org/10.1016/b978-0-32-391919-7.00006-8
https://doi.org/10.1016/b978-0-32-391919-7.00006-8
Publikováno v:
AI Assurance ISBN: 9780323919197
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4bc61b12ae5789c3bc36377a08030e93
https://doi.org/10.1016/b978-0-32-391919-7.00025-1
https://doi.org/10.1016/b978-0-32-391919-7.00025-1
Autor:
Yingjie Wang, Jaganmohan Chandrasekaran, Flora Haberkorn, Yan Dong, Munisamy Gopinath, Feras A. Batarseh
Publikováno v:
2022 IEEE 29th Annual Software Technology Conference (STC).
Publikováno v:
FEDS Notes. 2021
After collapsing in the second half of 2020, global demand for goods, as reflected in global trade, has been exceptionally strong and now well exceeds pre-pandemic levels. The sharp bounceback reflects several factors, including an unprecedented amou
Publikováno v:
FLAIRS Conference
Neural network algorithms have proven successful for accurate classifications in many domains such as image recognition and semantic parsing. However, they have long suffered from the lack of ability to measure causality, predict outliers effectively