44 citations · 364 across the 85 of their papers we have counts for
7 papers · 1 filter
Identifying Cognitive Radars -- Inverse Reinforcement Learning using Revealed Preferences
Vikram Krishnamurthy, Daniel Angley, Robin Evans +1
We consider an inverse reinforcement learning problem involving us versus an enemy radar equipped with a Bayesian tracker. By observing the emissions of the enemy radar,how can we…
What Did Your Adversary Believe? Optimal Filtering and Smoothing in Counter-Adversarial Autonomous Systems
Robert Mattila, Inês Lourenço, Vikram Krishnamurthy +2
We consider fixed-interval smoothing problems for counter-adversarial autonomous systems. An adversary deploys an autonomous filtering and control system that i) measures our curre…
Rationally Inattentive Inverse Reinforcement Learning Explains YouTube Commenting Behavior
William Hoiles, Vikram Krishnamurthy, Kunal Pattanayak
We consider a novel application of inverse reinforcement learning with behavioral economics constraints to model, learn and predict the commenting behavior of YouTube viewers. Each…
Maximum Likelihood Estimation of Power-law Degree Distributions via Friendship Paradox based Sampling
Buddhika Nettasinghe, Vikram Krishnamurthy
This paper considers the problem of estimating a power-law degree distribution of an undirected network using sampled data. Although power-law degree distributions are ubiquitous i…
Friendship Paradox Biases Perceptions in Directed Networks
Nazanin Alipourfard, Buddhika Nettasinghe, Andres Abeliuk +2
How popular a topic or an opinion appears to be in a network can be very different from its actual popularity. For example, in an online network of a social media platform, the num…
How to Calibrate your Adversary's Capabilities? Inverse Filtering for Counter-Autonomous Systems
Vikram Krishnamurthy, Muralidhar Rangaswamy
We consider an adversarial Bayesian signal processing problem involving "us" and an "adversary". The adversary observes our state in noise; updates its posterior distribution of th…
Convex Stochastic Dominance in Bayesian Localization, Filtering and Controlled Sensing POMDPs
Vikram Krishnamurthy
This paper provides conditions on the observation probability distribution in Bayesian localization and optimal filtering so that the conditional mean estimate satisfies convex sto…