9 papers
Anisotropic Tensor Deconvolution of Hyperspectral Images
Xinjue Wang, Xiuheng Wang, Esa Ollila +1
Hyperspectral image (HSI) deconvolution is a challenging ill-posed inverse problem, made difficult by the data's high dimensionality.We propose a parameter-parsimonious framework b…
Estimating Sequences with Memory for Minimizing Convex Non-smooth Composite Functions
Endrit Dosti, Sergiy A. Vorobyov, Themistoklis Charalambous
First-order optimization methods are crucial for solving large-scale data processing problems, particularly those involving convex non-smooth composite objectives. For such problem…
Generalized Nonnegative Structured Kruskal Tensor Regression
Xinjue Wang, Esa Ollila, Sergiy A. Vorobyov +1
This paper introduces Generalized Nonnegative Structured Kruskal Tensor Regression (NS-KTR), a novel tensor regression framework that enhances interpretability and performance thro…
Privacy-Preserving Quantized Federated Learning with Diverse Precision
Dang Qua Nguyen, Morteza Hashemi, Erik Perrins +3
Federated learning (FL) has emerged as a promising paradigm for distributed machine learning, enabling collaborative training of a global model across multiple local devices withou…
Wasserstein Distributionally Robust Adaptive Beamforming
Kiarash Hassas Irani, Sergiy A. Vorobyov, Yongwei Huang
Distributionally robust optimization (DRO)-based robust adaptive beamforming (RAB) enables enhanced robustness against model uncertainties, such as steering vector mismatches and i…
Pilot Contamination-Aware Graph Attention Network for Power Control in CFmMIMO
Tingting Zhang, Sergiy A. Vorobyov, David J. Love +2
Optimization-based power control algorithms are predominantly iterative with high computational complexity, making them impractical for real-time applications in cell-free massive…