activity
20082018
most citedWhere You Are Is Who You Are: User Identification by Matching Statistics

103 citations · 374 across the 10 of their papers we have counts for

collaborators

11 papers

eess.SP2018★ 11 cited

Joint Beamforming and Association Design for MIMO Radar

Urs Niesen, Jayakrishnan Unnikrishnan

A critical task of a radar receiver is data association, which assigns radar target detections to target filter tracks. Motivated by its importance, this paper introduces the probl…

cs.LG2015★ 103 cited

Where You Are Is Who You Are: User Identification by Matching Statistics

Farid M. Naini, Jayakrishnan Unnikrishnan, Patrick Thiran +1

Most users of online services have unique behavioral or usage patterns. These behavioral patterns can be exploited to identify and track users by using only the observed patterns i…

cs.IT2015

Unlabeled Sensing with Random Linear Measurements

Jayakrishnan Unnikrishnan, Saeid Haghighatshoar, Martin Vetterli

We study the problem of solving a linear sensing system when the observations are unlabeled. Specifically we seek a solution to a linear system of equations y = Ax when the order o…

cs.IT2014★ 40 cited

Asymptotically Optimal Matching of Multiple Sequences to Source Distributions and Training Sequences

Jayakrishnan Unnikrishnan

Consider a finite set of sources, each producing i.i.d. observations that follow a unique probability distribution on a finite alphabet. We study the problem of matching a finite s…

cs.IT2013★ 1 cited

On Minimal Trajectories for Mobile Sampling of Bandlimited Fields

Karlheinz Gröchenig, José Luis Romero, Jayakrishnan Unnikrishnan +1

We study the design of sampling trajectories for stable sampling and the reconstruction of bandlimited spatial fields using mobile sensors. The spectrum is assumed to be a symmetri…

cs.LG2013★ 33 cited

Approximate dynamic programming using fluid and diffusion approximations with applications to power management

Wei Chen, Dayu Huang, Ankur A. Kulkarni +5

Neuro-dynamic programming is a class of powerful techniques for approximating the solution to dynamic programming equations. In their most computationally attractive formulations,…

cs.MM2012★ 50 cited

Sampling and Reconstruction of Spatial Fields using Mobile Sensors

Jayakrishnan Unnikrishnan, Martin Vetterli

Spatial sampling is traditionally studied in a static setting where static sensors scattered around space take measurements of the spatial field at their locations. In this paper w…

cs.IT2011

Sampling High-Dimensional Bandlimited Fields on Low-Dimensional Manifolds

Jayakrishnan Unnikrishnan, Martin Vetterli

Consider the task of sampling and reconstructing a bandlimited spatial field in using moving sensors that take measurements along their path. It is inexpensive to increase…

cs.IT2009★ 83 cited

Minimax Robust Quickest Change Detection

Jayakrishnan Unnikrishnan, Venugopal V. Veeravalli, Sean Meyn

The popular criteria of optimality for quickest change detection procedures are the Lorden criterion, the Shiryaev-Roberts-Pollak criterion, and the Bayesian criterion. In this pap…

cs.IT2009★ 53 cited

Universal and Composite Hypothesis Testing via Mismatched Divergence

Jayakrishnan Unnikrishnan, Dayu Huang, Sean Meyn +2

For the universal hypothesis testing problem, where the goal is to decide between the known null hypothesis distribution and some other unknown distribution, Hoeffding proposed a u…

cs.NI2008

Algorithms for Dynamic Spectrum Access with Learning for Cognitive Radio

Jayakrishnan Unnikrishnan, Venugopal Veeravalli

We study the problem of dynamic spectrum sensing and access in cognitive radio systems as a partially observed Markov decision process (POMDP). A group of cognitive users cooperati…