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eess.SP2026
Total Variation Sparse Bayesian Learning for Block Sparsity via Majorization-Minimization
Yanbin He, Geethu Joseph
Block sparsity is a widely exploited structure in sparse recovery, offering significant gains when signal blocks are known. Yet, practical signals often exhibit unknown block bound…
eess.SP2024
Efficient Off-Grid Bayesian Parameter Estimation for Kronecker-Structured Signals
Yanbin He, Geethu Joseph
This work studies the problem of jointly estimating unknown parameters from Kronecker-structured multidimensional signals, which arises in applications like intelligent reflecting…
eess.SP2024
A Hierarchical View of Structured Sparsity in Kronecker Compressive Sensing
Yanbin He, Geethu Joseph
Kronecker compressed sensing refers to using Kronecker product matrices as sparsifying bases and measurement matrices in compressed sensing. This work focuses on the Kronecker comp…