206 citations · 854 across the 54 of their papers we have counts for
14 papers · 1 filter
Online Learning and Optimization of Markov Jump Affine Models
Sevi Baltaoglu, Lang Tong, Qing Zhao
The problem of online learning and optimization of unknown Markov jump affine models is considered. An online learning policy, referred to as Markovian simultaneous perturbations s…
Estimation after Parameter Selection: Performance Analysis and Estimation Methods
Tirza Routtenberg, Lang Tong
In many practical parameter estimation problems, prescreening and parameter selection are performed prior to estimation. In this paper, we consider the problem of estimating a pres…
Polytope Codes Against Adversaries in Networks
Oliver Kosut, Lang Tong, David Tse
Network coding is studied when an adversary controls a subset of nodes in the network of limited quantity but unknown location. This problem is shown to be more difficult than when…
The Embedding Capacity of Information Flows Under Renewal Traffic
Stefano Marano, Vincenzo Matta, Ting He +1
Given two independent point processes and a certain rule for matching points between them, what is the fraction of matched points over infinitely long streams? In many application…
Cognitive Coexistence between Infrastructure and Ad-hoc Systems
Stefan Geirhofer, Lang Tong, Brian M. Sadler
The rapid proliferation of wireless systems makes interference management more and more important. This paper presents a novel cognitive coexistence framework, which enables an inf…
Energy Scaling Laws for Distributed Inference in Random Fusion Networks
Animashree Anandkumar, Joseph E. Yukich, Lang Tong +1
The energy scaling laws of multihop data fusion networks for distributed inference are considered. The fusion network consists of randomly located sensors distributed i.i.d. accord…
Distributed Source Coding in the Presence of Byzantine Sensors
Oliver Kosut, Lang Tong
The distributed source coding problem is considered when the sensors, or encoders, are under Byzantine attack; that is, an unknown group of sensors have been reprogrammed by a mali…
Anonymous Networking amidst Eavesdroppers
Parvathinathan Venkitasubramaniam, Ting He, Lang Tong
The problem of security against timing based traffic analysis in wireless networks is considered in this work. An analytical measure of anonymity in eavesdropped networks is propos…
Detection of Gauss-Markov Random Fields with Nearest-Neighbor Dependency
Animashree Anandkumar, Lang Tong, Ananthram Swami
The problem of hypothesis testing against independence for a Gauss-Markov random field (GMRF) is analyzed. Assuming an acyclic dependency graph, an expression for the log-likelihoo…
Variable-Rate Distributed Source Coding in the Presence of Byzantine Sensors
Oliver Kosut, Lang Tong
The distributed source coding problem is considered when the sensors, or encoders, are under Byzantine attack; that is, an unknown number of sensors have been reprogrammed by a mal…
Capacity of Cooperative Fusion in the Presence of Byzantine Sensors
Oliver Kosut, Lang Tong
The problem of cooperative fusion in the presence of Byzantine sensors is considered. An information theoretic formulation is used to characterize the Shannon capacity of sensor fu…
Optimal and Suboptimal Detection of Gaussian Signals in Noise: Asymptotic Relative Efficiency
Youngchul Sung, Lang Tong, H. Vincent Poor
The performance of Bayesian detection of Gaussian signals using noisy observations is investigated via the error exponent for the average error probability. Under unknown signal co…
Neyman-Pearson Detection of Gauss-Markov Signals in Noise: Closed-Form Error Exponent and Properties
Youngchul Sung, Lang Tong, H. Vincent Poor
The performance of Neyman-Pearson detection of correlated stochastic signals using noisy observations is investigated via the error exponent for the miss probability with a fixed l…
A Large Deviations Approach to Sensor Scheduling for Detection of Correlated Random Fields
Youngchul Sung, Lang Tong, H. Vincent Poor
The problem of scheduling sensor transmissions for the detection of correlated random fields using spatially deployed sensors is considered. Using the large deviations principle, a…