Report NEP-BIG-2019-07-29

This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé issued this report. It is usually issued weekly.

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Other reports in NEP-BIG

The following items were announced in this report:

• Alexis Bogroff & Dominique Guégan, 2019. "Artificial Intelligence, Data, Ethics. An Holistic Approach for Risks and Regulation," Working Papers 2019: 19, Department of Economics, University of Venice "Ca' Foscari".
• Alex Burnap & John R. Hauser & Artem Timoshenko, 2019. "Product Aesthetic Design: A Machine Learning Augmentation," Papers 1907.07786, arXiv.org, revised Nov 2022.
• Songül Tolan, 2018. "Fair and Unbiased Algorithmic Decision Making: Current State and Future Challenges," JRC Working Papers on Digital Economy 2018-10, Joint Research Centre (Seville site).
• Arora, Gaurav & Rathore, Tushita & Gupta, Gargi & Anand, Saket, 2019. "Socioeconomic and Biophysical Drivers of Cropland Use Intensification in India: Analysis using satellite data and administrative surveys," 2019 Annual Meeting, July 21-23, Atlanta, Georgia 291104, Agricultural and Applied Economics Association.
• Felipe Carozzi & Sefi Roth, 2019. "Dirty density: air quality and the density of American cities," CEP Discussion Papers dp1635, Centre for Economic Performance, LSE.
• Brummelhuis, Raymond & Luo, Zhongmin, 2019. "Bank Net Interest Margin Forecasting and Capital Adequacy Stress Testing by Machine Learning Techniques," MPRA Paper 94779, University Library of Munich, Germany.
• Bucci, Andrea, 2019. "Cholesky-ANN models for predicting multivariate realized volatility," MPRA Paper 95137, University Library of Munich, Germany.
• Melia, Elvis, 2019. "The impact of information and communication technologies on jobs in Africa: a literature review," IDOS Discussion Papers 3/2019, German Institute of Development and Sustainability (IDOS).
• David Easley & Eleonora Patacchini & Christopher Rojas, 2019. "Multidimensional Diffusion Processes in Dynamic Online Networks," EIEF Working Papers Series 1912, Einaudi Institute for Economics and Finance (EIEF), revised Jul 2019.
• Bernard Lapeyre & J'er^ome Lelong, 2019. "Neural network regression for Bermudan option pricing," Papers 1907.06474, arXiv.org, revised Dec 2020.
• Souradeep Chakraborty, 2019. "Capturing Financial markets to apply Deep Reinforcement Learning," Papers 1907.04373, arXiv.org, revised Dec 2019.
• J. M. Calabuig & H. Falciani & E. A. S'anchez-P'erez, 2019. "Dreaming machine learning: Lipschitz extensions for reinforcement learning on financial markets," Papers 1907.05697, arXiv.org, revised Mar 2020.