165 citations · 717 across the 68 of their papers we have counts for
14 papers · 1 filter
Decentralized Decision-Making Over Multi-Task Networks
Sahar Khawatmi, Abdelhak M. Zoubir, Ali H. Sayed
In important applications involving multi-task networks with multiple objectives, agents in the network need to decide between these multiple objectives and reach an agreement abou…
Robust Bayesian Cluster Enumeration Based on the Distribution
Freweyni K. Teklehaymanot, Michael Muma, Abdelhak M. Zoubir
A major challenge in cluster analysis is that the number of data clusters is mostly unknown and it must be estimated prior to clustering the observed data. In real-world applicatio…
Minimax Optimal Sequential Hypothesis Tests for Markov Processes
Michael Fauss, Abdelhak M. Zoubir, H. Vincent Poor
Under mild Markov assumptions, sufficient conditions for strict minimax optimality of sequential tests for multiple hypotheses under distributional uncertainty are derived. First,…
Robust Distributed Cooperative RSS-based Localization for Directed Graphs in Mixed LoS/NLoS Environments
Luca Carlino, Di Jin, Michael Muma +1
The accurate and low-cost localization of sensors using a wireless sensor network is critically required in a wide range of today's applications. We propose a novel, robust maximum…
Toward Unobtrusive In-home Gait Analysis Based on Radar Micro-Doppler Signatures
Ann-Kathrin Seifert, Moeness G. Amin, Abdelhak M. Zoubir
Objective: In this paper, we demonstrate the applicability of radar for gait classification with application to home security, medical diagnosis, rehabilitation and assisted living…
Semiparametric Slepian-Bangs Formula for Complex Elliptically Symmetric Distributions
Stefano Fortunati, Abdelhak M. Zoubir, Fulvio Gini +1
This letter aims at deriving a Semiparametric Slepian-Bangs (SSB) formula for Complex Elliptically Symmetric (CES) distributed data vectors. The Semiparametric Cramér-Rao Bound (SC…
The Semiparametric Cramér-Rao Bound for Complex Elliptically Symmetric Distributions
Stefano Fortunati, Fulvio Gini, Maria S. Greco +1
This letter aims at extending the Constrained Semiparametric Cramer-Rao Bound (CSCRB) for the joint estimation of mean vector and scatter matrix of Real Elliptically Symmetric (RES…
Semiparametric Inference and Lower Bounds for Real Elliptically Symmetric Distributions
Stefano Fortunati, Fulvio Gini, Maria S. Greco +2
This paper has a twofold goal. The first aim is to provide a deeper understanding of the family of the Real Elliptically Symmetric (RES) distributions by investigating their intrin…
Bayesian Sequential Joint Detection and Estimation
Dominik Reinhard, Michael Fauss, Abdelhak M. Zoubir
Joint detection and estimation refers to deciding between two or more hypotheses and, depending on the test outcome, simultaneously estimating the unknown parameters of the underly…
Tight MMSE Bounds for the AGN Channel Under KL Divergence Constraints on the Input Distribution
Michael Fauss, Alex Dytso, Abdelhak M. Zoubir +1
Tight bounds on the minimum mean square error for the additive Gaussian noise channel are derived, when the input distribution is constrained to be epsilon-close to a Gaussian refe…
On the Equivalence of f-Divergence Balls and Density Bands in Robust Detection
Michael Fauss, Abdelhak M. Zoubir, H. Vincent Poor
The paper deals with minimax optimal statistical tests for two composite hypotheses, where each hypothesis is defined by a non-parametric uncertainty set of feasible distributions.…
Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling
Adrian Šošić, Elmar Rueckert, Jan Peters +2
Advances in the field of inverse reinforcement learning (IRL) have led to sophisticated inference frameworks that relax the original modeling assumption of observing an agent behav…
A fresh look at the Semiparametric Cramér-Rao Bound
Stefano Fortunati, Fulvio Gini, Maria S. Greco +2
This paper aims at providing a fresh look at semiparametric estimation theory and, in particular, at the Semiparametric Cramér-Rao Bound (SCRB). Semiparametric models are character…
Robust Sequential Detection in Distributed Sensor Networks
Mark R. Leonard, Abdelhak M. Zoubir
We consider the problem of sequential binary hypothesis testing with a distributed sensor network in a non-Gaussian noise environment. To this end, we present a general formulation…