Concept
Isthme (théorie des graphes)
Publications associées (40)
GAP: 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 ...
Berkeley2023Efficient Distributed Transposition Of Large-Scale Multigraphs And High-Cardinality Sparse Matrices
Felix Schürmann, Bruno Ricardo Da Cunha Magalhães
Graph-based representations underlie a wide range of scientific problems. Graph connectivity is typically represented as a sparse matrix in the Compressed Sparse Row format. Large-scale graphs rely on distributed storage, allocating distinct subsets of row ...
2020Buffer Placement and Sizing for High-Performance Dataflow Circuits
Paolo Ienne, Andrea Guerrieri, Lana Josipovic, Shabnam Sheikhha
Commercial high-level synthesis tools typically produce statically scheduled circuits. Yet, effective C-to-circuit conversion of arbitrary software applications calls for dataflow circuits, as they can handle efficiently variable latencies (e.g., caches) a ...
ASSOC COMPUTING MACHINERY2020Graph-based image representation learning
Though deep learning (DL) algorithms are very powerful for image processing tasks, they generally require a lot of data to reach their full potential. Furthermore, there is no straightforward way to impose various properties, given by the prior knowledge a ...
EPFL2019Hierarchical Routing Over Dynamic Wireless Networks
Matthias Grossglauser, Suhas Diggavi, Dominique Florian Tschopp
The topology of a mobile wireless network changes over time. Maintaining routes between all nodes requires the continuous transmission of control information, which consumes precious power and bandwidth resources. Many routing protocols have been developed ...
Wiley-Blackwell2015