activity
20172021
collaborators

7 papers

stat.ML2021

Non-Local Feature Aggregation on Graphs via Latent Fixed Data Structures

Mostafa Rahmani, Rasoul Shafipour, Ping Li

In contrast to image/text data whose order can be used to perform non-local feature aggregation in a straightforward way using the pooling layers, graphs lack the tensor representa…

eess.SP2020

Online Topology Inference from Streaming Stationary Graph Signals with Partial Connectivity Information

Rasoul Shafipour, Gonzalo Mateos

We develop online graph learning algorithms from streaming network data. Our goal is to track the (possibly) time-varying network topology, and effect memory and computational savi…

eess.SP2018

A Novel Scheme for Support Identification and Iterative Sampling of Bandlimited Graph Signals

Abolfazl Hashemi, Rasoul Shafipour, Haris Vikalo +1

We study the problem of sampling and reconstruction of bandlimited graph signals where the objective is to select a node subset of prescribed cardinality that ensures interpolation…

eess.SP2018

A Directed Graph Fourier Transform with Spread Frequency Components

Rasoul Shafipour, Ali Khodabakhsh, Gonzalo Mateos +1

We study the problem of constructing a graph Fourier transform (GFT) for directed graphs (digraphs), which decomposes graph signals into different modes of variation with respect t…

eess.SP2018

Blind Identification of Invertible Graph Filters with Multiple Sparse Inputs

Chang Ye, Rasoul Shafipour, Gonzalo Mateos

This paper deals with problem of blind identification of a graph filter and its sparse input signal, thus broadening the scope of classical blind deconvolution of temporal and spat…

stat.ML2017

Sampling and Reconstruction of Graph Signals via Weak Submodularity and Semidefinite Relaxation

Abolfazl Hashemi, Rasoul Shafipour, Haris Vikalo +1

We study the problem of sampling a bandlimited graph signal in the presence of noise, where the objective is to select a node subset of prescribed cardinality that minimizes the si…