Controlled Markov chains (CMCs) form the bedrock for model-based
reinfor...
We study sparse linear regression over a network of agents, modeled as a...
This paper considers data-driven chance-constrained stochastic optimizat...
In this article, we prove a Feynman-Kac type result for a broad class of...
Datasets displaying temporal dependencies abound in science and engineer...
We present methodology for estimating the stochastic intensity of a doub...
We study system design problems stated as parameterized stochastic progr...
This paper establishes the asymptotic consistency of the loss-calibrate...
We establish sharp tail asymptotics for component-wise extreme values of...
We study data-driven decision-making problems in a parametrized Bayesian...
We study stochastic programming models where the stochastic variable is ...
We study stochastic programming models where the stochastic variable is ...
In this work, we study consistency properties of α-Rényi approximate
pos...
The rise of e-hailing taxis has significantly altered urban transportati...
We consider a single stage stochastic program without recourse with a
st...
We quantify the large deviations of Gaussian extreme value statistics on...