
Bayesian Sequential Joint Detection and Estimation under Multiple Hypotheses
We consider the problem of jointly testing multiple hypotheses and estim...
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Distributed Joint Detection and Estimation: A Sequential Approach
We investigate the problem of jointly testing two hypotheses and estimat...
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Tight Bounds on the Weighted Sum of MMSEs with Applications in Distributed Estimation
In this paper, tight upper and lower bounds are derived on the weighted ...
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Decentralized DecisionMaking Over MultiTask Networks
In important applications involving multitask networks with multiple ob...
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Robust Bayesian Cluster Enumeration
A major challenge in cluster analysis is that the number of data cluster...
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Minimax Optimal Sequential Hypothesis Tests for Markov Processes
Under mild Markov assumptions, sufficient conditions for strict minimax ...
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Bayesian Sequential Joint Detection and Estimation
Joint detection and estimation refers to deciding between two or more hy...
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Tight MMSE Bounds for the AGN Channel Under KL Divergence Constraints on the Input Distribution
Tight bounds on the minimum mean square error for the additive Gaussian ...
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On the Equivalence of fDivergence Balls and Density Bands in Robust Detection
The paper deals with minimax optimal statistical tests for two composite...
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Inverse Reinforcement Learning via Nonparametric SpatioTemporal Subgoal Modeling
Recent advances in the field of inverse reinforcement learning (IRL) hav...
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Robust Sequential Detection in Distributed Sensor Networks
We consider the problem of sequential binary hypothesis testing with a d...
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A Novel Bayesian Cluster Enumeration Criterion for Unsupervised Learning
The Bayesian Information Criterion (BIC) has been widely used for estima...
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Bayesian Nonparametric Unmixing of Hyperspectral Images
Hyperspectral imaging is an important tool in remote sensing, allowing f...
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Bayesian Nonparametric Feature and Policy Learning for DecisionMaking
Learning from demonstrations has gained increasing interest in the recen...
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Decentralized Clustering and Linking by Networked Agents
We consider the problem of decentralized clustering and estimation over ...
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Dictionary Learning Strategies for Compressed Fiber Sensing Using a Probabilistic Sparse Model
We present a sparse estimation and dictionary learning framework for com...
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A Bayesian Approach to Policy Recognition and State Representation Learning
Learning from demonstration (LfD) is the process of building behavioral ...
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Inverse Reinforcement Learning in Swarm Systems
Inverse reinforcement learning (IRL) has become a useful tool for learni...
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Abdelhak M. Zoubir
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