9 citations · 21 across the 12 of their papers we have counts for
14 papers
Adaptive Learning via Off-Model Training and Importance Sampling for Fully Non-Markovian Optimal Stochastic Control. Complete version
Dorival Leão, Alberto Ohashi, Simone Scotti +1
This paper studies continuous-time stochastic control problems whose controlled states are fully non-Markovian and depend on unknown model parameters. Such problems arise naturally…
Sequential Regression Learning with Randomized Algorithms
Dorival Leão, Reiko Aoki, Alberto Ohashi +1
This paper presents ``randomized SINDy", a sequential machine learning algorithm designed for dynamic data that has a time-dependent structure. It employs a probabilistic approach,…
Data Analysis for Proficiency Testing
Reiko Aoki, Dorival Leão, Juan Pablo Mamani Bustamante +1
Proficiency Testing (PT) determines the performance of individual laboratories for specific tests or measurements and it is used to monitor the reliability of laboratories measurem…
Solving non-Markovian Stochastic Control Problems driven by Wiener Functionals
Dorival Leão, Alberto Ohashi, Francys Andrews de Souza
In this article, we present a general methodology for stochastic control problems driven by the Brownian motion filtration including non-Markovian and non-semimartingale state proc…
Estimation of Distribution Algorithm for Protein Structure Prediction
Daniel Bonetti, Alexandre Delbem, Dorival Leão +1
Proteins are essential for maintaining life. For example, knowing the structure of a protein, cell regulatory mechanisms of organisms can be modeled, supporting the development of…
Weak differentiability of Wiener functionals and occupation times
Dorival Leão, Alberto Ohashi, Alexandre B. Simas
In this paper, we establish a universal variational characterization of the non-martingale components associated with weakly differentiable Wiener functionals in the sense of Leão,…