Support Vector Machines（支持向量机）和Deep Learning（深度学习）等技术可以更加有效率地处理复杂关系。
California, and Emeritus Professor of Economics, University of California, Berkeley, California.不...
2019. The impact of machine learning on economics. In Agrawal, Gans, and Goldfarb Eds. The Economics of Artificial Intelligence: An Agenda. University of Chicago Press.Athey, Susan. 2018. The impact of machine learning on economics. In Agrawal, Gans, and Goldfarb Eds. The Economics of ...
doi:10.2139/ssrn.3012602DSGEAsset PricingDynamic ProgrammingMachine LearningThis paper proposes a global algorithm to solve a large class of nonlinear continuous-time models in finance and economics. Using tools from machine learning, ISocial Science Electronic Publishing...
The Impact of AI on Business, Economics and Innovation In addition, we highlight the importance; benefits and applications of Machine Learning in business shall be applied. Finally, the conclusions propose a future research agenda for AI for certain industries (Strategy, Relationship Marketing,... ...
Machine learning specialists are often primarily concerned with developing high-performance computer ...
作者:Jannes Klaas 出版社:Packt Publishing - ebooks Account 副标题:Data algorithms for the markets and deep learning from the ground up for financial experts and economics 出版年:2018-9-11 页数:300 定价:GBP 37.99 装帧:Paperback ISBN:9781789136364 ...
His recent research revolves around applications of machine learning tools in financial economics. Tony Guida is executive director at RAM Active Investments. He serves as chair of the machineByte think tank and is the author of Big Data and Machine Learning in Quantitative Investme... (展开全部...
Federated Learning: Strategies for Improving Communication Efficiency Bacon, "Federated learning: Strategies for improving communication efficiency," in Private Multi-Party Machine Learning (NIPS 2016 Workshop), pp. 1-6, ... Jakub Konen,HB Mcmahan,FX Yu,... 被引量: 137发表: 2016年 ReasoNet: ...
This study provides a comprehensive review of machine learning (ML) applications in the fields of business and finance. First, it introduces the most commonly used ML techniques and explores their diverse applications in marketing, stock analysis, demand