6 papers · 1 filter
Closed-Loop Identification of Stabilized Models Using Dual Input-Output Parameterization
Ran Chen, Amber Srivastava, Mingzhou Yin +1
This paper introduces a dual input-output parameterization (dual IOP) for the identification of linear time-invariant systems from closed-loop data. It draws inspiration from the r…
A Dual System-Level Parameterization for Identification from Closed-Loop Data
Amber Srivastava, Mingzhou Yin, Andrea Iannelli +1
This work presents a dual system-level parameterization (D-SLP) method for closed-loop system identification. The recent system-level synthesis framework parameterizes all stabiliz…
Time-Varying Parameters in Sequential Decision Making Problems
Amber Srivastava, S. M. Salapaka
In this paper we address the class of Sequential Decision Making (SDM) problems that are characterized by time-varying parameters. These parameter dynamics are either pre-specified…
Design of Experiments with Imputable Feature Data: An Entropy-Based Approach
Raj K. Velicheti, Amber Srivastava, Srinivasa M. Salapaka
Tactical selection of experiments to estimate an underlying model is an innate task across various fields. Since each experiment has costs associated with it, selecting statistical…
Inequality Constraints in Facility Location and Other Similar Optimization Problems: An Entropy Based Approach
Amber Srivastava, Gabriel Barsi Haberfeld, Naira Hovakimyan +1
In this paper we propose an annealing based framework to incorporate inequality constraints in optimization problems such as facility location, simultaneous facility location with…
Multiway k-Cut in Static and Dynamic Graphs: A Maximum Entropy Principle Approach
Mayank Baranwal, Amber Srivastava, Srinivasa Salapaka
This work presents a maximum entropy principle based algorithm for solving minimum multiway -cut problem defined over static and dynamic {\em digraphs}. A multiway -cut probl…