Publication
Degree-constrained edge partitioning in graphs arising from discrete tomography
Publications associées (283)
The Power of Two Matrices in Spectral Algorithms for Community Recovery
Spectral algorithms are some of the main tools in optimization and inference problems on graphs. Typically, the graph is encoded as a matrix and eigenvectors and eigenvalues of the matrix are then used to solve the given graph problem. Spectral algorithms ...
Ieee-Inst Electrical Electronics Engineers Inc2024The connection of the acyclic disconnection and feedback arc sets - On an open problem of Figueroa et al.
We examine the connection of two graph parameters, the size of a minimum feedback arcs set and the acyclic disconnection. A feedback arc set of a directed graph is a subset of arcs such that after deletion the graph becomes acyclic. The acyclic disconnecti ...
Elsevier2024Recovering Static and Time-Varying Communities Using Persistent Edges
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This article focuses on spectral methods for recovering communities in temporal networks. In the case of fixed communities, spectral clustering on the simple time-aggregated graph (i.e., the weighted graph formed by the sum of the interactions over all tem ...
Ieee Computer Soc2024A Distributed Augmenting Path Approach for the Bottleneck Assignment Problem
We develop an algorithm to solve the bottleneck assignment problem (BAP) that is amenable to having computation distributed over a network of agents. This consists of exploring how each component of the algorithm can be distributed, with a focus on one com ...
Piscataway2024In Medio Stat Virtus: Combining Boolean and Pattern Matching
Giovanni De Micheli, Alessandro Tempia Calvino, Gianluca Radi
Technology mapping transforms a technology-independent representation into a technology-dependent one given a library of cells. This process is performed by means of local replacements that are extracted by matching sections of the subject graph to library ...
2024SAT-based Exact Modulo Scheduling Mapping for Resource-Constrained CGRAs
David Atienza Alonso, Giovanni Ansaloni, José Angel Miranda Calero, Rubén Rodríguez Álvarez, Juan Pablo Sapriza Araujo, Benoît Walter Denkinger
Coarse-Grain Reconfigurable Arrays (CGRAs) represent emerging low-power architectures designed to accelerate Compute-Intensive Loops (CILs). The effectiveness of CGRAs in providing acceleration relies on the quality of mapping: how efficiently the CIL is c ...
2024A full characterization of invariant embeddability of unimodular planar graphs
When can a unimodular random planar graph be drawn in the Euclidean or the hyperbolic plane in a way that the distribution of the random drawing is isometry-invariant? This question was answered for one-ended unimodular graphs in Benjamini and Timar, using ...
WILEY2023Metastability of the Potts Ferromagnet on Random Regular Graphs
We study the performance of Markov chains for the q-state ferromagnetic Potts model on random regular graphs. While the cases of the grid and the complete graph are by now well-understood, the case of random regular graphs has resisted a detailed analysis ...
SPRINGER2023GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation
Daniel Gatica-Perez, Sina Sajadmanesh
In this paper, we study the problem of learning Graph Neural Networks (GNNs) with Differential Privacy (DP). We propose a novel differentially private GNN based on Aggregation Perturbation (GAP), which adds stochastic noise to the GNN's aggregation functio ...
Berkeley2023Privatized graph federated learning
Ali H. Sayed, Stefan Vlaski, Elsa Rizk
Federated learning is a semi-distributed algorithm, where a server communicates with multiple dispersed clients to learn a global model. The federated architecture is not robust and is sensitive to communication and computational overloads due to its one-m ...
SPRINGER2023