24 citations · 63 across the 25 of their papers we have counts for
30 papers
Stochastic Dynamics of Low Earth Orbit Near Full Capacity
Priyank Behera, Aditya S. Gopalan, Harsha Honnappa
The capacity of Low Earth Orbit (LEO) to sustain space operations is under mounting pressure from megaconstellations, legacy fragmentation debris, and new payload classes. Existing…
The Small-Noise Limit of the Most Likely Element is the Most Likely Element in the Small-Noise Limit
Zachary Selk, Harsha Honnappa
In this paper, we study the Onsager-Machlup function and its relationship to the Freidlin-Wentzell function for measures equivalent to arbitrary infinite dimensional Gaussian measu…
Distributed Sparse Regression via Penalization
Yao Ji, Gesualdo Scutari, Ying Sun +1
We study sparse linear regression over a network of agents, modeled as an undirected graph (with no centralized node). The estimation problem is formulated as the minimization of t…
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…
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…
Bayesian Joint Chance Constrained Optimization: Approximations and Statistical Consistency
Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao
This paper considers data-driven chance-constrained stochastic optimization problems in a Bayesian framework. Bayesian posteriors afford a principled mechanism to incorporate data…
PAC-Bayes Bounds on Variational Tempered Posteriors for Markov Models
Imon Banerjee, Vinayak A. Rao, Harsha Honnappa
Datasets displaying temporal dependencies abound in science and engineering applications, with Markov models representing a simplified and popular view of the temporal dependence s…
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…
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…
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…
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…
A Many-Server Functional Strong Law For A Non-Stationary Loss Model
Prakash Chakraborty, Harsha Honnappa
The purpose of this note is to show that it is possible to establish a many-server functional strong law of large numbers (FSLLN) for the fraction of occupied servers (i.e., the sc…
Asymptotic Consistency of Loss-Calibrated Variational Bayes
Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao
This paper establishes the asymptotic consistency of the {\it loss-calibrated variational Bayes} (LCVB) method. LCVB was proposed in~\cite{LaSiGh2011} as a method for approximately…
Strong Embeddings for Transitory Queueing Models
Prakash Chakraborty, Harsha Honnappa
In this paper we establish strong embedding theorems, in the sense of the Komlos-Major-Tusnady framework, for the performance metrics of a general class of transitory queueing mode…
Large Deviations of Bivariate Gaussian Extrema
Remco van der Hofstad, Harsha Honnappa
We establish sharp tail asymptotics for component-wise extreme values of bivariate Gaussian random vectors with arbitrary correlation between the components. We consider two scalin…
On the Statistical Consistency of Risk-Sensitive Bayesian Decision-Making
Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao
We study data-driven decision-making problems in the Bayesian framework, where the expectation in the Bayes risk is replaced by a risk-sensitive entropic risk measure. We focus on…
Asymptotic Consistency of Rényi-Approximate Posteriors
Prateek Jaiswal, Vinayak A. Rao, Harsha Honnappa
We study the asymptotic consistency properties of -Rényi approximate posteriors, a class of variational Bayesian methods that approximate an intractable Bayesian posterior with…
Modeling Urban Taxi Services with e-hailings: A Queueing Network Approach
Wenbo Zhang, Harsha Honnappa, Satish V. Ukkusuri
The rise of e-hailing taxis has significantly altered urban transportation and resulted in a competitive taxi market with both traditional street-hailing and e-hailing taxis. The n…
Optimal Allocations for Sample Average Approximation
Prateek Jaiswal, Harsha Honnappa, Raghu Pasupathy
We consider a single stage stochastic program without recourse with a strictly convex loss function. We assume a compact decision space and grid it with a finite set of points. In…
Dominating Points of Gaussian Extremes
Harsha Honnappa, Raghu Pasupathy, Prateek Jaiswal
We quantify the large deviations of Gaussian extreme value statistics on closed convex sets in d-dimensional Euclidean space. The asymptotics imply that the extreme value distribut…
An optimal control approach of day-to-day congestion pricing for stochastic transportation networks
Hemant Gehlot, Harsha Honnappa, Satish V. Ukkusuri
Congestion pricing has become an effective instrument for traffic demand management on road networks. This paper proposes an optimal control approach for congestion pricing for day…
Approximating Performance Measures for Slowly Changing Non-stationary Markov Chains
Zeyu Zheng, Harsha Honnappa, Peter W. Glynn
This paper is concerned with the development of rigorous approximations to various expectations associated with Markov chains and processes having non-stationary transition probabi…
Conditioned Functional Limits and Applications to Queues
Harsha Honnappa, Rahul Jain, Amy R. Ward
We consider a renewal process that is conditioned on the number of events in a fixed time horizon. We prove that a centered and scaled version of this process converges to a Browni…
Transitory Queueing Networks
Harsha Honnappa, Rahul Jain
Queueing networks are notoriously difficult to analyze sans both Markovian and stationarity assumptions. Much of the theoretical contribution towards performance analysis of time-i…