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van der Meulen, P.Q. (author), Coutino, Mario (author), Bosch, Johannes G. (author), Kruizinga, P. (author), Leus, G.J.T. (author)We consider the scenario of finding the transfer function of an aberrating layer in front of a receiving ultrasound (US) array, assuming a separate non-aberrated transmit source. We propose a method for blindly estimating this transfer function without exact knowledge of the ultrasound sources or acoustic contrast image, and without directly...journal article 2023
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Kokke, C.A. (author), Coutino, Mario (author), Anitori, Laura (author), Heusdens, R. (author), Leus, G.J.T. (author)Sensor selection is a useful method to help reduce data throughput, as well as computational, power, and hardware requirements, while still maintaining acceptable performance. Although minimizing the Cramér-Rao bound has been adopted previously for sparse sensing, it did not consider multiple targets and unknown source models. In this work, we...conference paper 2023
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Kokke, C.A. (author), Coutino, Mario (author), Heusdens, R. (author), Leus, G.J.T. (author)Sensor selection is a useful method to help reduce computational, hardware, and power requirements while maintaining acceptable performance. Although minimizing the Cramér-Rao bound has been adopted previously for sparse sensing, it did not consider multiple targets and unknown target directions. We propose to tackle the sensor selection problem...conference paper 2023
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Yang, Qiuling (author), Coutino, Mario (author), Leus, G.J.T. (author), Giannakis, Georgios B. (author)Graph-based learning and estimation are fundamental problems in various applications involving power, social, and brain networks, to name a few. While learning pair-wise interactions in network data is a well-studied problem, discovering higher-order interactions among subsets of nodes is still not yet fully explored. To this end, encompassing...journal article 2023
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Coutino, Mario (author), Leus, G.J.T. (author)One of the main challenges of graph filters is the stability of their design. While classical graph filters allow for a stable design using optimal polynomial approximation theory, generalized graph filters tend to suffer from the ill-conditioning of the involved system matrix. This issue, accentuated for increasing graph filter orders,...journal article 2022
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Natali, A. (author), Isufi, E. (author), Coutino, Mario (author), Leus, G.J.T. (author)This work proposes an algorithmic framework to learn time-varying graphs from online data. The generality offered by the framework renders it model-independent, i.e., it can be theoretically analyzed in its abstract formulation and then instantiated under a variety of model-dependent graph learning problems. This is possible by phrasing (time...journal article 2022
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He, Y. (author), Coutino, Mario (author), Isufi, E. (author), Leus, G.J.T. (author)In this work, we focus on partitioning dynamic graphs with two types of nodes (bi-colored), though not necessarily bipartite graphs. They commonly appear in communication network applications, e.g., one color being base stations, the other users, and the dynamic process being the varying connection status between base stations and moving...conference paper 2022
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Kokke, C.A. (author), Coutino, Mario (author), Heusdens, R. (author), Leus, G.J.T. (author), Anitori, L. (author)Doppler velocity estimation in pulse-Doppler radar is done by evaluating the target returns of bursts of pulses. While this provides convenience and accuracy, it requires multiple pulses. In adaptive and cognitive radar systems, the ability to adapt on consecutive pulses, instead of bursts, brings potential performance benefits. Hence, with...conference paper 2022
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Yang, Maosheng (author), Coutino, Mario (author), Leus, G.J.T. (author), Isufi, E. (author)A critical task in graph signal processing is to estimate the true signal from noisy observations over a subset of nodes, also known as the reconstruction problem. In this paper, we propose a node-adaptive regularization for graph signal reconstruction, which surmounts the conventional Tikhonov regularization, giving rise to more degrees of...journal article 2021
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Leus, G.J.T. (author), Yang, Maosheng (author), Coutino, Mario (author), Isufi, E. (author)To deal with high-dimensional data, graph filters have shown their power in both graph signal processing and data science. However, graph filters process signals exploiting only pairwise interactions between the nodes, and they are not able to exploit more complicated topological structures. Graph Volterra models, on the other hand, are also...conference paper 2021
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Natali, A. (author), Coutino, Mario (author), Isufi, E. (author), Leus, G.J.T. (author)Signal processing and machine learning algorithms for data sup-ported over graphs, require the knowledge of the graph topology. Unless this information is given by the physics of the problem (e.g., water supply networks, power grids), the topology has to be learned from data. Topology identification is a challenging task, as the problem is often...conference paper 2021
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Natali, A. (author), Isufi, E. (author), Coutino, Mario (author), Leus, G.J.T. (author)Topology identification is an important problem across many disciplines, since it reveals pairwise interactions among entities and can be used to interpret graph data. In many scenarios, however, this (unknown) topology is time-varying, rendering the problem even harder. In this paper, we focus on a time-varying version of the structural...conference paper 2021
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Li, Bingcong (author), Coutino, Mario (author), Giannakis, Georgios B. (author), Leus, G.J.T. (author)With the well-documented popularity of Frank Wolfe (FW) algorithms in machine learning tasks, the present paper establishes links between FW subproblems and the notion of momentum emerging in accelerated gradient methods (AGMs). On the one hand, these links reveal why momentum is unlikely to be effective for FW-type algorithms on general...journal article 2021
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Sharma, Shubham (author), Coutino, Mario (author), Chepuri, Sundeep Prabhakar (author), Leus, G.J.T. (author), Hari, K. V.S. (author)The design of feasible trajectories to traverse the k-space for sampling in magnetic resonance imaging (MRI) is important while considering ways to reduce the scan time. Over the recent years, non-Cartesian trajectories have been observed to result in benign artifacts and being less sensitive to motion. In this paper, we propose a generalized...journal article 2020
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Coutino, Mario (author), Isufi, E. (author), Maehara, T. (author), Leus, G.J.T. (author)In this work, we explore the state-space formulation of network processes to recover the underlying network structure (local connections). To do so, we employ subspace techniques borrowed from system identification literature and extend them to the network topology inference problem. This approach provides a unified view of the traditional...conference paper 2020
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Li, Qiongxiu (author), Coutino, Mario (author), Leus, G.J.T. (author), Christensen, M. Graesboll (author)With an increasingly interconnected and digitized world, distributed signal processing and graph signal processing have been proposed to process its big amount of data. However, privacy has become one of the biggest challenges holding back the widespread adoption of these tools for processing sensitive data. As a step towards a solution, we...conference paper 2020
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Coutino, Mario (author), Isufi, E. (author), Maehara, Takanori (author), Leus, G.J.T. (author)In this article, we explore the state-space formulation of a network process to recover from partial observations the network topology that drives its dynamics. To do so, we employ subspace techniques borrowed from system identification literature and extend them to the network topology identification problem. This approach provides a unified...journal article 2020
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Coutino, Mario (author), Chepuri, Sundeep Prabhakar (author), Maehara, Takanori (author), Leus, G.J.T. (author)To analyze and synthesize signals on networks or graphs, Fourier theory has been extended to irregular domains, leading to a so-called graph Fourier transform. Unfortunately, different from the traditional Fourier transform, each graph exhibits a different graph Fourier transform. Therefore to analyze the graph-frequency domain properties of...journal article 2020
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Tohidi, E. (author), Amiri, Rouhollah (author), Coutino, Mario (author), Gesbert, David (author), Leus, G.J.T. (author), Karbasi, Amin (author)Submodularity is a discrete domain functional property that can be interpreted as mimicking the role of well-known convexity/concavity properties in the continuous domain. Submodular functions exhibit strong structure that lead to efficient optimization algorithms with provable near-optimality guarantees. These characteristics, namely,...journal article 2020
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Yang, M. (author), Coutino, Mario (author), Isufi, E. (author), Leus, G.J.T. (author)While regularization on graphs has been successful for signal reconstruction, strategies for controlling the bias-variance trade-off of such methods have not been completely explored. In this work, we put forth a node varying regularizer for graph signal reconstruction and develop a minmax approach to design the vector of regularization...conference paper 2020
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