2 citations · 2 across the 11 of their papers we have counts for
5 papers · 1 filter
Channel-Informed Neural Network for Physical Layer Key Generation
Jose Angel Sanchez Viloria, George Sklivanitis, Dimitris Pados +1
Physical-layer key generation (PKG) enables wireless devices to establish shared keys from reciprocal channel observations without directly exchanging the key. This capability is a…
Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition
Georgios I. Orfanidis, Dimitris A. Pados, George Sklivanitis +1
Motivated by sensing modalities in modern autonomous systems that involve hardware-constrained spatial sampling over large arrays with limited coherence time, we develop a novel fr…
Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation
Georgios I. Orfanidis, Dimitris A. Pados, George Sklivanitis +1
We consider the problems of computing the optimal rank-1 Hankel and Toeplitz-structured approximation of arbitrary matrices under L2 and L1-norm error. Such problems arise naturall…
Kernel Regression of Multi-Way Data via Tensor Trains with Hadamard Overparametrization: The Dynamic Graph Flow Case
Duc Thien Nguyen, Konstantinos Slavakis, Eleftherios Kofidis +1
A regression-based framework for interpretable multi-way data imputation, termed Kernel Regression via Tensor Trains with Hadamard overparametrization (KReTTaH), is introduced. KRe…
Imputation of Time-varying Edge Flows in Graphs by Multilinear Kernel Regression and Manifold Learning
Duc Thien Nguyen, Konstantinos Slavakis, Dimitris Pados
This paper extends the recently developed framework of multilinear kernel regression and imputation via manifold learning (MultiL-KRIM) to impute time-varying edge flows in a graph…