Search Results for author: Mario Coutino

Found 9 papers, 2 papers with code

Revisiting Matching Pursuit: Beyond Approximate Submodularity

no code implementations12 May 2023 Ehsan Tohidi, Mario Coutino, David Gesbert

We study the problem of selecting a subset of vectors from a large set, to obtain the best signal representation over a family of functions.

Run-Time Monitors Design for Adaptive Radar Systems: A Practical Framework

no code implementations20 Feb 2023 Pepijn Cox, Mario Coutino, Giuseppe Papari, Ahmad Mouri Sardarabadi, Laura Anitori

The proposed framework can be used by radar practitioners and researchers for applying run-time-verification to adaptive, re-configurable radar systems.

Self-Driving Cars

Learning Time-Varying Graphs from Online Data

no code implementations21 Oct 2021 Alberto Natali, Elvin Isufi, Mario Coutino, Geert Leus

This work proposes an algorithmic framework to learn time-varying graphs from online data.

Graph Learning

Online Time-Varying Topology Identification via Prediction-Correction Algorithms

no code implementations22 Oct 2020 Alberto Natali, Mario Coutino, Elvin Isufi, Geert Leus

Signal processing and machine learning algorithms for data supported over graphs, require the knowledge of the graph topology.

Topology-Aware Joint Graph Filter and Edge Weight Identification for Network Processes

no code implementations7 Jul 2020 Alberto Natali, Mario Coutino, Geert Leus

Therefore, in this paper, we focus on the joint identification of coefficients and graph weights defining the graph filter that best models the observed input/output network data.

How Does Momentum Help Frank Wolfe?

no code implementations19 Jun 2020 Bingcong Li, Mario Coutino, Georgios B. Giannakis, Geert Leus

We unveil the connections between Frank Wolfe (FW) type algorithms and the momentum in Accelerated Gradient Methods (AGM).

Submodularity in Action: From Machine Learning to Signal Processing Applications

no code implementations17 Jun 2020 Ehsan Tohidi, Rouhollah Amiri, Mario Coutino, David Gesbert, Geert Leus, Amin Karbasi

We introduce a variety of submodular-friendly applications, and elucidate the relation of submodularity to convexity and concavity which enables efficient optimization.

BIG-bench Machine Learning

Sampling and Reconstruction of Signals on Product Graphs

2 code implementations30 Jun 2018 Guillermo Ortiz-Jiménez, Mario Coutino, Sundeep Prabhakar Chepuri, Geert Leus

In this paper, we consider the problem of subsampling and reconstruction of signals that reside on the vertices of a product graph, such as sensor network time series, genomic signals, or product ratings in a social network.

Active Learning Recommendation Systems +2

Sparse Sampling for Inverse Problems with Tensors

2 code implementations28 Jun 2018 Guillermo Ortiz-Jiménez, Mario Coutino, Sundeep Prabhakar Chepuri, Geert Leus

We consider the problem of designing sparse sampling strategies for multidomain signals, which can be represented using tensors that admit a known multilinear decomposition.

Information Theory Signal Processing Information Theory

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