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20212025
most citedA Statistical Decision-Theoretical Perspective on the Two-Stage Approach to Parameter Estimation

4 citations · 8 across the 10 of their papers we have counts for

collaborators

10 papers

math.OC2025

Gain-Scheduled Data-Enabled Predictive Control: A DeePC Approach for Nonlinear Systems

Margarita A. Guerrero, Braghadeesh Lakshminarayanan, Cristian R. Rojas

Model predictive control is a well established control technology for trajectory tracking. Its use requires the availability of an accurate model of the plant, but obtaining such a…

eess.SY2025

On Asymptotic Analysis of the Two-Stage Approach: Towards Data-Driven Parameter Estimation

Braghadeesh Lakshminarayanan, Cristian R. Rojas

In this paper, we analyze the asymptotic properties of the Two-Stage (TS) estimator -- a simulation-based parameter estimation method that constructs estimators offline from synthe…

eess.SY2025

A Metropolis-Adjusted Langevin Algorithm for Sampling Jeffreys Prior

Yibo Shi, Braghadeesh Lakshminarayanan, Cristian R. Rojas

Inference and estimation are fundamental in statistics, system identification, and machine learning. When prior knowledge about the system is available, Bayesian analysis provides…

eess.SY2025

Fine Tuning a Simulation-Driven Estimator

Braghadeesh Lakshminarayanan, Margarita A. Guerrero, Cristian R. Rojas

Many industries now deploy high-fidelity simulators (digital twins) to represent physical systems, yet their parameters must be calibrated to match the true system. This motivated…

eess.SY2025★ 2 cited

Data-Driven Estimation of Structured Singular Values

Margarita A. Guerrero, Braghadeesh Lakshminarayanan, Cristian R. Rojas

Estimating the size of the modeling error is crucial for robust control. Over the years, numerous metrics have been developed to quantify the model error in a control relevant mann…

stat.ME2023

Minimax Two-Stage Gradient Boosting for Parameter Estimation

Braghadeesh Lakshminarayanan, Cristian R. Rojas

Parameter estimation is an important sub-field in statistics and system identification. Various methods for parameter estimation have been proposed in the literature, among which t…

eess.SY2023

Unraveling the Control Engineer's Craft with Neural Networks

Braghadeesh Lakshminarayanan, Federico Dettù, Cristian R. Rojas +1

Many industrial processes require suitable controllers to meet their performance requirements. More often, a sophisticated digital twin is available, which is a highly complex mode…

math.OC2022

A Unified Approach to Differentially Private Bayes Point Estimation

Braghadeesh Lakshminarayanan, Cristian R. Rojas

Parameter estimation in statistics and system identification relies on data that may contain sensitive information. To protect this sensitive information, the notion of \emph{diffe…

stat.ME2022★ 4 cited

A Statistical Decision-Theoretical Perspective on the Two-Stage Approach to Parameter Estimation

Braghadeesh Lakshminarayanan, Cristian R. Rojas

One of the most important problems in system identification and statistics is how to estimate the unknown parameters of a given model. Optimization methods and specialized procedur…

cs.LG2021★ 2 cited

Bandit Quickest Changepoint Detection

Aditya Gopalan, Venkatesh Saligrama, Braghadeesh Lakshminarayanan

Many industrial and security applications employ a suite of sensors for detecting abrupt changes in temporal behavior patterns. These abrupt changes typically manifest locally, ren…