Gobet, EmmanuelLópez-Salas, José GermánVázquez, Carlos2019-08-302019-08-302019-08-06GOBET, Emmanuel; SALAS, José Germán López; VÁZQUEZ, Carlos. Quasi-Regression Monte-Carlo Method for Semi-Linear PDEs and BSDEs. En Multidisciplinary Digital Publishing Institute Proceedings. 2019. p. 44.2504-3900http://hdl.handle.net/2183/23895[Abstract] In this work we design a novel and efficient quasi-regression Monte Carlo algorithm in order to approximate the solution of discrete time backward stochastic differential equations (BSDEs), and we analyze the convergence of the proposed method. With the challenge of tackling problems in high dimensions we propose suitable projections of the solution and efficient parallelizations of the algorithm taking advantage of powerful many core processors such as graphics processing units (GPUs).engAtribución 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/BSDEsSemi-linear PDEsParallel computingGPUsCUDAQuasi-Regression Monte-Carlo Method for Semi-Linear PDEs and BSDEsconference outputopen access10.3390/proceedings2019021044