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05/23/2023
Deep-Learning-Aided Alternating Least Squares for Tensor CP Decomposition and Its Application to Massive MIMO Channel Estimation
CANDECOMP/PARAFAC (CP) decomposition is the mostly used model to formula...
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10/27/2022
Forecasting Graph Signals with Recursive MIMO Graph Filters
Forecasting time series on graphs is a fundamental problem in graph sign...
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10/21/2022
Blind Polynomial Regression
Fitting a polynomial to observed data is an ubiquitous task in many sign...
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01/27/2022
Simplicial Convolutional Filters
We study linear filters for processing signals supported on abstract top...
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10/21/2021
Learning Time-Varying Graphs from Online Data
This work proposes an algorithmic framework to learn time-varying graphs...
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10/06/2021
Simplicial Convolutional Neural Networks
Graphs can model networked data by representing them as nodes and their ...
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03/23/2021
Finite Impulse Response Filters for Simplicial Complexes
In this paper, we study linear filters to process signals defined on sim...
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10/22/2020
Online Time-Varying Topology Identification via Prediction-Correction Algorithms
Signal processing and machine learning algorithms for data supported ove...
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06/19/2020
How Does Momentum Help Frank Wolfe?
We unveil the connections between Frank Wolfe (FW) type algorithms and t...
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04/17/2020
Forecasting Multi-Dimensional Processes over Graphs
The forecasting of multi-variate time processes through graph-based tech...
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03/08/2020
Graphs, Convolutions, and Neural Networks
Network data can be conveniently modeled as a graph signal, where data v...
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11/08/2019
Learning Connectivity and Higher-order Interactions in Radial Distribution Grids
To perform any meaningful optimization task, distribution grid operators...
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06/26/2019
Low-Complexity Equalization of MIMO-OSDM
Orthogonal signal-division multiplexing (OSDM) is an attractive alternat...
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12/04/2018
Joint Ranging and Clock Synchronization for Dense Heterogeneous IoT Networks
Synchronization and ranging in internet of things (IoT) networks are cha...
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12/03/2018
Online Graph-Adaptive Learning with Scalability and Privacy
Graphs are widely adopted for modeling complex systems, including financ...
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06/30/2018
Sampling and Reconstruction of Signals on Product Graphs
In this paper, we consider the problem of subsampling and reconstruction...
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06/28/2018
Sparse Sampling for Inverse Problems with Tensors
We consider the problem of designing sparse sampling strategies for mult...
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05/22/2018
Joint Detection and Localization of an Unknown Number of Sources Using Algebraic Structure of the Noise Subspace
Source localization and spectral estimation are among the most fundament...
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05/01/2018
Convolutional Neural Networks Architectures for Signals Supported on Graphs
We describe two architectures that generalize convolutional neural netwo...
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03/06/2018
MIMO Graph Filters for Convolutional Neural Networks
Superior performance and ease of implementation have fostered the adopti...
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10/27/2017
Convolutional Neural Networks Via Node-Varying Graph Filters
Convolutional neural networks (CNNs) are being applied to an increasing ...
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02/14/2016
Autoregressive Moving Average Graph Filtering
One of the cornerstones of the field of signal processing on graphs are ...
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09/10/2013