Reservoir computing: Forecasting and filtering of financial time series. Joint Universität Konstanz & Universität Sankt Gallen Workshop on Computational Social Science. St. Gallen, Switzerland, December 20.
Singular ridge regression with homoscedastic residuals: generalization error with estimated parameters. Statistische Woche. Augsburg, September 15.
Reservoir computing: information processing of stationary signals. The 19th IEEE International Conference on Computational Science and Engineering (CSE 2016). Ecole de Mines. Paris, August 25. Best Paper Award.
Volatility forecasting using global stochastic financial trends extracted from non-synchronous data. Research Seminar, Chair of Statistics, Augsburg, Germany, June 9.
Volatility forecasting using global stochastic financial trends extracted from non-synchronous data. Konstanz-Strasbourg Workshop “Applied Econometrics”, Moos, Germany, October 9.
Estimation and empirical performance of non-scalar dynamic conditional correlation models. Mathematical and Computational Finance Laboratory (MCFL) at the Department of Mathematics and Statistics, University of Calgary, Canada, July 8.
Volatility and time series forecasting with non-scalar parametric models and machine-learning based techniques. University of Konstanz, Konstanz, Germany, May 5.
Reservoir computing: optimal nonlinear information processing capacity, performance, and universality. Applications to stochastic nonlinear time series forecasting. Journée du Laboratoire de Mathématiques, Besançon, France, January 8.
Grigoryeva, L., Henriques, J., Larger, L., Ortega, J.-P. 2013. Stochastic nonlinear time series forecasting using time-delay reservoir computers: performance and universality. Workshop: Experimental Reservoir Computing, Besançon, France, October, 14-15.
Bauwens, L., Grigoryeva, L. , Ortega, J.-P. 2013. Estimation and empirical performance of non-scalar DCC models. CORE-ILSM Lecture Series, Louvain-la-Neuve, Belgium, September 30-October 2.
Grigoryeva, L. , Ortega, J.-P. 2013. Estimation of sizeable matrix based DCC models via Bregman divergences. CEQURA-2013, Munich, Germany, September, 23-24.
Grigoryeva, L. , Ortega, J.-P. 2013. Hybrid forecasting with estimated temporally aggregated linear processes. IwCEE: International workshop on Computational Economics and Econometrics, Rome, Italy, June, 12-13.
Grygor’yeva, L. 2010. Mathematical modelling of static and dynamic configurations of magnetically interacting rigid bodies. Seminar On Differential Equations: Masaryk University (Faculty of Science, Department of Mathematics and Statistics), Brno, Czech Republic, November 15.
Grygor’yeva, L. V., Kozoriz, V. V. 2008. Maple-exploring of a free flywheel suspended by super-conductive bearing. Maglev 2008: Proceedings of The 20th International Conference on Magnetically Levitated Systems and Linear Drives, San Diego, USA, December, 15-18.
Grygor’yeva, L. V., Kozoriz, V. V. 2008. On one generalization in two-body problem for motion in central and non-central physical fields. Proceedings of The 9th Crimean International Mathematical School Lyapunov Functions Method and Applications, Alushta, Ukraine, September, 15-21. (in Russian)
Grygor’yeva, L. V., Kozoriz, V. V., Tyagulskyi, V. G. 2008. On stability of static and dynamic configurations with a free body in Magnetic Potential Well. Stab08: Proceedings of the 10th International E.S. Pyatnitskiy Symposium ”Stability and Vibrations of Nonlinear Control Systems”, Moscow, Russia, June, 3-6. (in Russian)
Grygor’yeva, L. V. 2008. Models of dynamic magnetically interacting free bodies and Maple-analysis. Proceedings of the XIIth International Scientific M. Kravchuk Conference, Kyiv, Ukraine, May, 15-17. (in Ukrainian)
Grygor’yeva, L. V. 2007. MAPLE-modeling of some dynamical problems of magnetically interacting bodies. DSMSI 2007: Thesis of Conference Reports of Dynamical System Modelling and Stability Investigation, Kyiv, Ukraine, May, 22-25.