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Report NEP-BIG-2021-09-06
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:
- Marcelo Cajias & Willwersch Jonas & Lorenz Felix & Franz Fuerst, 2021, "Peeking inside the Black Box: Interpretable Machine Learning and Hedonic Rental Estimation," ERES, European Real Estate Society (ERES), number eres2021_104, Jan.
- Lisa Crosato & Caterina Liberati & Marco Repetto, 2021, "Look Who's Talking: Interpretable Machine Learning for Assessing Italian SMEs Credit Default," Papers, arXiv.org, number 2108.13914, Aug, revised Sep 2021.
- Andres, Antonio Rodriguez & Otero, Abraham & Amavilah, Voxi Heinrich, 2021, "Evaluation of technology clubs by clustering: A cautionary note," MPRA Paper, University Library of Munich, Germany, number 109138, May.
- Dat Thanh Tran & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2021, "Bilinear Input Normalization for Neural Networks in Financial Forecasting," Papers, arXiv.org, number 2109.00983, Sep.
- Benedict von Ahlefeldt-Dehn & Marcelo Cajias & Wolfgang Schäfers, 2021, "The Future of Commercial Real Estate Market Research: A Case for Applying Machine Learning," ERES, European Real Estate Society (ERES), number eres2021_49, Jan.
- Philipp Maximilian Mueller & Björn-Martin Kurzrock, 2021, "Document Classification for Machine Learning in Real Estate Professional Services – Results of the Property Research Trust Project," ERES, European Real Estate Society (ERES), number eres2021_65, Jan.
- Juergen Deppner & Marcelo Cajias & Wolfgang Schäfers, 2021, "Accounting for Spatial Autocorrelation in Algorithm-Driven Hedonic Models: A Spatial Cross-Validation Approach," ERES, European Real Estate Society (ERES), number eres2021_51, Jan.
- Snehalkumar & S. Gaikwad & Shankar Iyer & Dalton Lunga & Yu-Ru Lin, 2021, "Proceedings of KDD 2020 Workshop on Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning," Papers, arXiv.org, number 2109.00435, Sep, revised Sep 2021.
- Boris Babic & Daniel L. Chen & Theodoros Evgeniou & Anne-Laure Fayard, 2021, "Onboarding AI," Post-Print, HAL, number hal-03276433.
- Matthias Soot & Sabine Horvath & Hans-Berndt Neuner & Alexandra Weitkamp, 2021, "Analysis of Property Yields for Multi-Family Houses with Spatial Method and ANN," ERES, European Real Estate Society (ERES), number eres2021_44, Jan.
- Haataja, Meeri & Bryson, Joanna J., 2021, "What costs should we expect from the EU’s AI Act?," SocArXiv, Center for Open Science, number 8nzb4, Aug, DOI: 10.31219/osf.io/8nzb4.