Département : Information, Opérations et Sciences de la Décision
Associate Professor
s.nyawa@tbs-education.fr
DE WAAL, H., S. NYAWA, S. FOSSO WAMBA, "Consumers’ Financial Distress: Prediction and Prescription Using Interpretable Machine Learning", Information Systems Frontiers, 2024 [fnege: 3, abs: 3]
GNEKPE, C., D. TCHUENTE, S. NYAWA, P. K. DEY, "Energy Performance of Building Refurbishments: Predictive and Prescriptive AI-based Machine Learning Approaches", Journal of Business Research, 2024, vol. 183, pp. 114821 [fnege: 2, abs: 3]
NYAWA, S., C. GNEKPE, D. TCHUENTE, "Transparent machine learning models for predicting decisions to undertake energy retrofits in residential buildings", Annals of Operations Research, 2023 [fnege: 2, abs: 3]
TCHUENTE, D., S. NYAWA, "Real estate price estimation in French cities using geocoding and machine learning", Annals of Operations Research, 2022, vol. 308, pp. 571–608 [cnrs: 2, fnege: 2, abs: 3]
NYAWA, S., D. TCHUENTE, S. FOSSO WAMBA, "COVID-19 vaccine hesitancy: a social media analysis using deep learning", Annals of Operations Research, 2022 [cnrs: 2, fnege: 2, abs: 3]
TCHUENTE, D., S. NYAWA, S. FOSSO WAMBA, "COVID-19 Vaccine Global Information Management Through Bibliometrics", Journal of Global Information Management, 2021, vol. 29, no. 6, pp. 1-22 [cnrs: 3, fnege: 3, abs: 2]
BOLLERSLEV, T., N. MEDDAHI, S. NYAWA, "High-dimensional multivariate realizedvolatility estimation", Journal of Econometrics, 2019, vol. 212, no. 1, pp. 116-136 [cnrs: 1, abs: 4]
NYAWA, S., "On the Connection Between Threshold Models and Trees’ Regressions: Application to Volatility’s Forecasting" dans Conférence Econométrie financière, 14/06/2024,, 2024
NYAWA, S., "Consumers' Financial Wellbeing: Prediction of Financial Rehabilitation Using Machine Learning" dans Conférence Data and AI in Social Sciences, 17/06/2024, Yaoundé, 2024
NYAWA, S., "Machine Learning for Digital Mobile Banking Adoption" dans Conférence ICT4, novembre, 2024, Yaoundé
SULLIVAN, Y., S. NYAWA, S. FOSSO WAMBA, "Combating Loneliness with Artificial Intelligence: An AI-Based Emotional Support Model" dans Proceedings of the 56th Hawaii International Conference on System Sciences, pp. 4443-4453, 2023, Maui, Hawaii, Etats-Unis d'Amérique
NYAWA, S., "Consumers financial distress: Prediction and prescription using machine learning", 2023, Prague, République tchèque
NYAWA, S., "A Factor Model for systemic risk using Mutually Exciting Jump Processes" dans Econometric Society European Winter Meeting 2017, Barcelona, Spain, 12-13 December, 2017
NYAWA, S., "A Factor Model for systemic risk using Mutually Exciting Jump Processes" dans French Econometric Conference, Paris, France, 30 Novembre - 1er Décembre 2017, 2017
NYAWA, S., T. BOLLERSLEV, N. MEDDAHI, "High-Dimensional Multivariate Realized Volatility Estimation" dans Society of Financial Econometrics Conference, New York, USA, June 2017, 2017
NYAWA, S., T. BOLLERSLEV, N. MEDDAHI, "High-Dimensional Multivariate Realized Volatility Estimation" dans Big Data in Dynamic Predictive Econometric Modeling, Pennsylvania, 18-19 Mai, 2017
NYAWA, S., N. MEDDAHI, T. BOLLERSLEY, "High-Dimensional Multivariate Realized Volatility Estimation" dans 10th Financial Risks International Forum 2017, Paris, France, 27-28 mars, 2017
NYAWA, S., T. BOLLERSLEV, N. MEDDAHI, "High Dimensional Multivariate Realized Volatility Measures" dans Vienna Financial Econometrics Conference, Vienna, 9-11 mars, 2017 co-auteurs présentés
NYAWA, S., T. BOLLERSLEV, N. MEDDAHI, "High Dimensional Multivariate Realized Volatility Measures" dans 27th (EC)2 Conference on Big Data Toulouse, 16-17 Décembre, 2016
NYAWA, S., T. BOLLERSLEV, N. MEDDAHI, "High Dimensional Multivariate Realized Volatility Measures" dans Recent Advances in Econometrics, Toulouse, France, 28-29 Juin, 2016
NYAWA, S., T. BOLLERSLEV, N. MEDDAHI, "High Dimensional Multivariate Realized Volatility Measures" dans EEA-ESEM 2016 Conference, Geneve, switzerland , 22-26 août, 2016
CARILLO, K., S. AKTER, K. ALNOFELI, T. BEGUM, D. TCHUENTE, N. CHAUDHURI, S. FOSSO WAMBA, S. NYAWA, "Handbook of Big Data Research Methods" dans Research Handbooks in Information Systems., Ed., Edward Elgar Publishing, vol. 3, 2023
DE WALL, H., S. NYAWA, S. FOSSO WAMBA, "Consumers Financial Distress: Prediction and Prescription Using Machine Learning" dans Dynamics of Information Systems., Hossein Moosaei, Milan Hladík, Panos M. Pardalos Eds, Springer Nature Switzerland, pp. 218-231, 2023
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Cet article présente l’estimation des prix de l’immobilier en France, un marché peu étudié. Nous comparons sept techniques d’apprentissage automatique populaires en proposant une approche différente qui quantifie la pertinence des caractéristiques de localisation.