64 citations · 410 across the 142 of their papers we have counts for
9 papers · 2 filters
Stability and Sample Complexity of Divergence Regularized Optimal Transport
Erhan Bayraktar, Stephan Eckstein, Xin Zhang
We study stability and sample complexity properties of divergence regularized optimal transport (DOT). First, we obtain quantitative stability results for optimizers of DOT measure…
Finite Approximations for Mean Field Type Multi-Agent Control and Their Near Optimality
Erhan Bayraktar, Nicole Bauerle, Ali Devran Kara
We study a multi-agent mean field type control problem in discrete time where the agents aim to find a socially optimal strategy and where the state and action spaces for the agent…
A neural network approach to high-dimensional optimal switching problems with jumps in energy markets
Erhan Bayraktar, Asaf Cohen, April Nellis
We develop a backward-in-time machine learning algorithm that uses a sequence of neural networks to solve optimal switching problems in energy production, where electricity and fos…
Data-Driven Nonparametric Robust Control under Dependence Uncertainty
Erhan Bayraktar, Tao Chen
We consider a multi-period stochastic control problem where the multivariate driving stochastic factor of the system has known marginal distributions but uncertain dependence struc…
A smooth variational principle on Wasserstein space
Erhan Bayraktar, Ibrahim Ekren, Xin Zhang
In this note, we provide a smooth variational principle on Wasserstein space by constructing a smooth gauge-type function using the sliced Wasserstein distance. This function is a…
A Rank-Based Reward between a Principal and a Field of Agents: Application to Energy Savings
Clémence Alasseur, Erhan Bayraktar, Roxana Dumitrescu +1
In this paper, we consider the problem of a Principal aiming at designing a reward function for a population of heterogeneous agents. We construct an incentive based on the ranking…
Stability of Equilibria in Time-inconsistent Stopping Problems
Erhan Bayraktar, Zhenhua Wang, Zhou Zhou
We investigate the stability of equilibrium-induced optimal values with respect to (w.r.t.) reward functions and transition kernels for time-inconsistent stopping problems…
Nonparametric Adaptive Robust Control Under Model Uncertainty
Erhan Bayraktar, Tao Chen
We consider a discrete time stochastic Markovian control problem under model uncertainty. Such uncertainty not only comes from the fact that the true probability law of the underly…
Approximate Q-Learning for Controlled Diffusion Processes and its Near Optimality
Erhan Bayraktar, Ali Devran Kara
We study a Q learning algorithm for continuous time stochastic control problems. The proposed algorithm uses the sampled state process by discretizing the state and control action…