32 citations · 46 across the 17 of their papers we have counts for
6 papers · 1 filter
Reinforced optimal control
Christian Bayer, Denis Belomestny, Paul Hager +3
Least squares Monte Carlo methods are a popular numerical approximation method for solving stochastic control problems. Based on dynamic programming, their key feature is the appro…
Short dated smile under Rough Volatility: asymptotics and numerics
Peter K. Friz, Paul Gassiat, Paolo Pigato
In [Precise Asymptotics for Robust Stochastic Volatility Models; Ann. Appl. Probab. 2021] we introduce a new methodology to analyze large classes of (classical and rough) stochasti…
Drift estimation of the threshold Ornstein-Uhlenbeck process from continuous and discrete observations
Sara Mazzonetto, Paolo Pigato
We refer by threshold Ornstein-Uhlenbeck to a continuous-time threshold autoregressive process. It follows the Ornstein-Uhlenbeck dynamics when above or below a fixed level, yet at…
Hybrid Template Canonical Correlation Analysis Method for Enhancing SSVEP Recognition under data-limited Condition
Runfeng Miao, Li Zhang, Qiang Sun
In this study, an advanced CCA-based algorithn called hybrid template canonical correlation analysis (HTCCA) was proposed to improve the performance of brain-computer interface (BC…
Density estimates and short-time asymptotics for a hypoelliptic diffusion process
Paolo Pigato
We study a system of differential equations, each in dimension . Only the first equation is forced by a Brownian motion and the dependence structure is such that, under a lo…
Randomized optimal stopping algorithms and their convergence analysis
Christian Bayer, Denis Belomestny, Paul Hager +2
In this paper we study randomized optimal stopping problems and consider corresponding forward and backward Monte Carlo based optimisation algorithms. In particular we prove the co…