Mario Bravo

Ph.D. en Matemáticas Aplicadas

Profesor Hora

FACULTAD DE INGENIERÍA Y CIENCIAS

CHILE

Stgo

Mario Bravo

El académico Mario Bravo es Ph.D. en Matemáticas Aplicadas de la Universidad Pierre et Marie Curie, en Francia; Magíster en Matemáticas Aplicadas de la misma casa de estudios e ingeniero civil matemático con Magíster en Transporte, de la Universidad de Chile. Su investigación se centra en la teoría de juegos en matemáticas aplicadas, algoritmos de aproximación estocástica, aplicaciones a optimización, entre otros. Se incorporó a la Facultad de Ingeniería y Ciencias de la Universidad Adolfo Ibáñez en 2021. Anteriormente, el profesor Bravo se desempeñó como profesor en la Universidad de Santiago de Chile. Mario Bravo se ha adjudicado varios proyectos Fondecyt y becas CONICYT, junto con una beca entregada por el gobierno de Francia para realizar estudios de doctorado.

Mario Bravo

Mario Bravo

Mario Bravo

Mario Bravo

Stochastic Halpern iteration in normed spaces and applications to reinforcement learning</>

Mixing Times and Privacy Analysis for the Projected Langevin Algorithm under a Modulus of Continuity</>

Near-Optimal Sample Complexity for MDPs via Anchoring</>

STOCHASTIC FIXED-POINT ITERATIONS FOR NONEXPANSIVE MAPS</>

UNIVERSAL BOUNDS FOR FIXED POINT ITERATIONS VIA OPTIMAL TRANSPORT METRICS</>

Learning with minimal information in continuous games</>

Rates of convergence for inexact Krasnosel’skii–Mann iterations in Banach spaces</>

Sharp convergence rates for averaged nonexpansive maps</>

Bandit learning in concave n-person games</>

On the robustness of learning in games with stochastically perturbed payoff observations</>

An adjusted payoff-based procedure for normal form games</>

Reinforcement learning with restrictions on the action set</>

An integrated behavioral model of the land-use and transport systems with network congestion and location externalities</>

Convergence and nonconvergence in discrete-time stochastic iterations</>

Dynamics and learning with partial interactions</>

Adaptive procedures in games and population dynamics: methods and applications </>

Information and Computation in Market Design</>

Stochastic Fixed Point Iterations and Reinforcement Learning</>

Stochastic Halpern iteration in normed spaces and applications to reinforcement learning</>

Mixing Times and Privacy Analysis for the Projected Langevin Algorithm under a Modulus of Continuity</>

Near-Optimal Sample Complexity for MDPs via Anchoring</>

STOCHASTIC FIXED-POINT ITERATIONS FOR NONEXPANSIVE MAPS</>

UNIVERSAL BOUNDS FOR FIXED POINT ITERATIONS VIA OPTIMAL TRANSPORT METRICS</>

Learning with minimal information in continuous games</>

Rates of convergence for inexact Krasnosel’skii–Mann iterations in Banach spaces</>

Sharp convergence rates for averaged nonexpansive maps</>

Bandit learning in concave n-person games</>

On the robustness of learning in games with stochastically perturbed payoff observations</>

An adjusted payoff-based procedure for normal form games</>

Reinforcement learning with restrictions on the action set</>

An integrated behavioral model of the land-use and transport systems with network congestion and location externalities</>

Convergence and nonconvergence in discrete-time stochastic iterations</>

Dynamics and learning with partial interactions</>

Adaptive procedures in games and population dynamics: methods and applications </>

Information and Computation in Market Design</>

Stochastic Fixed Point Iterations and Reinforcement Learning</>