Adland, R., Jia, H., & Strandenes, S. P. (2017, March 28). Are AIS-based trade volume estimates reliable? The case of. Maritime Policy & Management,44(5), 657-665. Retrieved from http://dx.doi.org/10.1080/03088839.2017.1309470
Alberg, J., & Lipton, Z. C. (2018, April 26). Improving Factor-Based Quantitative Investing by Forecasting Company Fundamentals. Retrieved from arxiv: https://arxiv.org/abs/1711.04837
Ball, R., & Brown, P. (1968). An empirical evaluation of accounting income numbers. Journal of Accounting Research,6(2), 159-178.
Banker, R. D., Khavis, J., & Park, H.-U. (2018, March 25). Crowdsourced Earnings Forecasts: Implications for Analyst Forecast Timing and Market Efficiency. Retrieved from SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3057388
Benamar, H., Foucault, T., & Vega, C. (2018, May 3). Demand for Information, Macroeconomic Uncertainty, and the Response of U.S. Treasury Securities to News. Retrieved from SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3162292
Bojanowski, P., Grave, E., Joulin, A., & Mikolov, T. (2016, June 7). Enriching Word Vectors with Subword Information. Retrieved from arxiv: https://arxiv.org/abs/1607.04606
Cavallo, A., & Rigobon, R. (2016). The Billion Prices Project: Using Online Prices for Measurement and Research. Journal of Economic Perspectives,30(2), 151–178.
Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018, Oct 11). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Retrieved from arXiv: https://arxiv.org/abs/1810.04805
Dumoulin, V., & Visin, F. (2018, January 11). A guide to convolution arithmetic for deep learning. Retrieved from arxiv: https://arxiv.org/abs/1603.07285
Eagle Alpha. (2018). Alternative Data Use Cases Edition 6. Eagle Alpha.
ElBahrawy, A., Alessandretti, L., & Baronchelli, A. (2019, April 1). Wikipedia and Digital Currencies: Interplay Between Collective Attention and Market Performance. Retrieved from SSRN: https://ssrn.com/abstract=3346632
Exante Data. (2018). Exante China FX Intervention Models.
Ghoshal, S., & Roberts, S. (2016). Extracting Predictive Information from Heterogeneous Data Streams using Gaussian Processes. Retrieved from arxiv: https://arxiv.org/abs/1603.06202
Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition. Springer.
Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013, September 7). Efficient Estimation of Word Representations in Vector Space. Retrieved from arxiv: https://arxiv.org/abs/1301.3781
Mikolov, T., Sutskever, I., Chen, K., Corrado, G., & Dean, J. (2013, October 16). Distributed Representations of Words and Phrases and their Compositionality. Retrieved from arxiv.org: https://arxiv.org/abs/1310.4546
Montjoye, Y.-A. d., Hidalgo, C. A., Verleysen, M., & Blondel, V. D. (2013, March 25). Unique in the Crowd: The privacy bounds of human mobility. Retrieved from Scientific Reports: https://www.nature.com/articles/srep01376
Murphy, K. P. (2012). Machine Learning: A Probabilistic Perspective. MIT Press.
Muschalle A., Stahl, F., Löser, A., Vossen, G. (2013). Pricing Approaches for Data Markets. In: Castellanos M., Dayal U., Rundensteiner E.A. (eds) Enabling Real-Time Business Intelligence. BIRTE 2012. Lecture Notes in Business Information Processing, vol 154. Springer, Berlin, Heidelberg.
Nie, J., & Oksol, A. (2018). Forecasting Current-Quarter U.S.Exports Using Satellite Data. Federal Reserve Bank of Kansas City (Q II), 5-24. Retrieved from Federal Reserve Bank of Kansas City: https://ideas.repec.org/a/fip/fedker/00065.html
Passarella, R. (2019, May 1). If Data is the new Oil - we should think about the industry as: Upstream - Exploration & Production, Mid-Stream - Transport & Storage, & Down Stream - Refining & the Customer … this way we know where the players fit. Retrieved from Twitter: https://twitter.com/robpas/status/1123658427056705536?
Pearl, J. (2009). Causal inference in statistics: An overview. Statist. Surv. 3, 96-146.
Petkar, H. (2016, October). A Review of Challenges in Automatic Speech. International Journal of Computer Applications,151(3), 23-26.
Rasmussen C. E. (2004). Gaussian Processes in Machine Learning. In: Bousquet O., von Luxburg U., Rätsch G. (eds) Advanced Lectures on Machine Learning. ML 2003. Lecture Notes in Computer Science, vol 3176. Springer, Berlin, Heidelberg.
Rocher, L., Hendrickx, J. M., & Montjoye, Y.-A. d. (2019, July 23). Estimating the success of re-identifications in incomplete datasets using generative models. Retrieved from Nature: https://www.nature.com/articles/s41467-019-10933-3/
Salahat, E., & Qasaimeh, M. (2017, March 17). Recent Advances in Features Extraction and Description Algorithms: A Comprehensive Survey. Retrieved from arxiv: https://arxiv.org/abs/1703.06376
Schaffer, C. (1994). A conservation law for generalization performance. International Conference on Machine Learning, H. Willian and W. Cohen, Editors. San Francisco: Morgan Kaufmann, pp. 259–265.
Sleptsova, E., Tukker, M., & Fennessy, R. (2019, May 3). A new tool for managing currency risk. Retrieved from Oxford Economics.
Sugiyama, M., Suzuki, T., & Kanamori, T.. (2012). Density Ratio Estimation in Machine Learning. Cambridge University.
Standage, T. (2014). Writing on the Wall: The Intriguing History of Social Media, from Ancient Rome to the Present Day. Bloomsbury Paperbacks.
Strohmeier, M., Smith, M., Lenders, V., & Martinovic, I. (2018, April 24). The Real First Class? Inferring Confidential Corporate Mergers and Government Relations from Air Traffic Communication. Retrieved from IEEE: https://ieeexplore.ieee.org/document/8406594
Wolpert, D. H. (2002). NThe Supervised Learning No—Free—Lunch Theorems. In: Roy R., Köppen M., Ovaska S., Furuhashi T., Hoffmann F. (eds) Soft Computing and Industry. Springer, London.
Young, T., Hazarika, D., Poria, S., & Cambria, E. (2018, November 25). Recent Trends in Deep Learning Based Natural Language Processing. Retrieved from arXiv.org: https://arxiv.org/abs/1708.02709
Zuckerman, G. (2019). The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution. Penguin.