activity
20172021
most citedOn Gaussian Limits and Large Deviations for Queues Fed by High Intensity Randomly Scattered Traffic

2 citations · 6 across the 9 of their papers we have counts for

collaborators

20 papers

math.PR2021

Diffusion Approximations for Queues In A Fast Oscillatory Random Environment

Harsha Honnappa, Yiran Liu, Samy Tindel +1

We study infinite server queues driven by Cox processes in a fast oscillatory random environment. While exact performance analysis is difficult, we establish diffusion approximatio…

math.CA20211 cited

A Feynman-Kac Type Theorem for ODEs: Solutions of Second Order ODEs as Modes of Diffusions

Zachary Selk, Harsha Honnappa

In this article, we prove a Feynman-Kac type result for a broad class of second order ordinary differential equations. The classical Feynman-Kac theorem says that the solution to a…

math.PR2020

Information Projection on Banach spaces with Applications to State Independent KL-Weighted Optimal Control

Zachary Selk, William Haskell, Harsha Honnappa

This paper studies constrained information projections on Banach spaces with respect to a Gaussian reference measure. Specifically our interest lies in characterizing projections o…

stat.ML20201 cited

Estimating Stochastic Poisson Intensities Using Deep Latent Models

Ruixin Wang, Prateek Jaiwal, Harsha Honnappa

We present methodology for estimating the stochastic intensity of a doubly stochastic Poisson process. Statistical and theoretical analyses of traffic traces show that these proces…

math.PR2020

Infinite server queues in a random fast oscillatory environment

Harsha Honnappa, Yiran Liu, Samy Tindel +1

In this paper, we consider a infinite server queueing model in a random environment. More specifically, the arrival rate in our server is modeled as a highly fluct…

stat.ML20201 cited

Variational Bayesian Methods for Stochastically Constrained System Design Problems

Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao

We study system design problems stated as parameterized stochastic programs with a chance-constraint set. We adopt a Bayesian approach that requires the computation of a posterior…