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Report NEP-BIG-2024-10-07
This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé (Tom Coupe) issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-BIG
The following items were announced in this report:
- Ina Ganguli & Jeffrey Lin & Vitaly Meursault & Nicholas F. Reynolds, 2024, "Patent Text and Long-Run Innovation Dynamics: The Critical Role of Model Selection," NBER Working Papers, National Bureau of Economic Research, Inc, number 32934, Sep.
- Prudence Djagba & Callixte Ndizihiwe, 2024, "Pricing American Options using Machine Learning Algorithms," Papers, arXiv.org, number 2409.03204, Sep.
- Abbaszadehpeivasti, Hadi, 2024, "Performance analysis of optimization methods for machine learning," Other publications TiSEM, Tilburg University, School of Economics and Management, number 3050a62d-1a1f-494e-99ef-7.
- Zhizhuo Kou & Holam Yu & Junyu Luo & Jingshu Peng & Xujia Li & Chengzhong Liu & Juntao Dai & Lei Chen & Sirui Han & Yike Guo, 2024, "Automate Strategy Finding with LLM in Quant Investment," Papers, arXiv.org, number 2409.06289, Sep, revised Nov 2025.
- Huaqing Xie & Xingcheng Xu & Fangjia Yan & Xun Qian & Yanqing Yang, 2024, "Deep Learning for Multi-Country GDP Prediction: A Study of Model Performance and Data Impact," Papers, arXiv.org, number 2409.02551, Sep.
- Meena Jagadeesan & Michael I. Jordan & Jacob Steinhardt, 2024, "Safety vs. Performance: How Multi-Objective Learning Reduces Barriers to Market Entry," Papers, arXiv.org, number 2409.03734, Sep.
- Sushant More & Priya Kotwal & Sujith Chappidi & Dinesh Mandalapu & Chris Khawand, 2024, "Double Machine Learning at Scale to Predict Causal Impact of Customer Actions," Papers, arXiv.org, number 2409.02332, Sep.
- Mengyu Wang & Tiejun Ma, 2024, "MANA-Net: Mitigating Aggregated Sentiment Homogenization with News Weighting for Enhanced Market Prediction," Papers, arXiv.org, number 2409.05698, Sep.
- Margherita Borella & Francisco Bullano & Mariacristina De Nardi & Benjamin Krueger & Elena Manresa, 2024, "Health Inequality and Health Types," Opportunity and Inclusive Growth Institute Working Papers, Federal Reserve Bank of Minneapolis, number 097, Aug, DOI: 10.21034/iwp.97.
- Gary Cornwall & Marina Gindelsky, 2024, "Nowcasting Distributional National Accounts for the United States: A Machine Learning Approach," BEA Papers, Bureau of Economic Analysis, number 0130, Sep.
- Guillermo Guzmán Prudencio & Lykke E. Andersen, 2023, "The most attractive municipalities in Bolivia: an analysis with electricity consumption data and satellite images," SDSN Bolivia, Universidad Privada Boliviana, number 06-23, Oct.
- Senst, Benjamin, 2024, "Data mining and NLP for Processing Social Offers of a National Aid Organization," SocArXiv, Center for Open Science, number 3pd4s, Sep, DOI: 10.31219/osf.io/3pd4s.
- Thomas Chalaux & Dave Turner, 2024, "Doombot versus other machine-learning methods for evaluating recession risks in OECD countries," OECD Economics Department Working Papers, OECD Publishing, number 1821, Sep, DOI: 10.1787/1a8c0a92-en.