135 citations · 234 across the 30 of their papers we have counts for
11 papers · 1 filter
Bounding the Difference between the Values of Robust and Non-Robust Markov Decision Problems
Ariel Neufeld, Julian Sester
In this note we provide an upper bound for the difference between the value function of a distributionally robust Markov decision problem and the value function of a non-robust Mar…
Feasible approximation of matching equilibria for large-scale matching for teams problems
Ariel Neufeld, Qikun Xiang
We propose a numerical algorithm for computing feasible and approximately optimal solutions of the matching for teams problem. Specifically, we introduce the notion of approximate…
Langevin dynamics based algorithm e-THO POULA for stochastic optimization problems with discontinuous stochastic gradient
Dong-Young Lim, Ariel Neufeld, Sotirios Sabanis +1
We introduce a new Langevin dynamics based algorithm, called e-THO POULA, to solve optimization problems with discontinuous stochastic gradients which naturally appear…
Markov Decision Processes under Model Uncertainty
Ariel Neufeld, Julian Sester, Mario Šikić
We introduce a general framework for Markov decision problems under model uncertainty in a discrete-time infinite horizon setting. By providing a dynamic programming principle we o…
Numerical method for approximately optimal solutions of two-stage distributionally robust optimization with marginal constraints
Ariel Neufeld, Qikun Xiang
We consider a general class of two-stage distributionally robust optimization (DRO) problems where the ambiguity set is constrained by fixed marginal probability laws that are not…
Numerical method for feasible and approximately optimal solutions of multi-marginal optimal transport beyond discrete measures
Ariel Neufeld, Qikun Xiang
We propose a numerical algorithm for the computation of multi-marginal optimal transport (MMOT) problems involving general probability measures that are not necessarily discrete. B…