Concept

Bridge (graph theory)

Related publications (40)

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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 ...

Berkeley2023

Efficient 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 ...

2020

Buffer 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 MACHINERY2020

Graph-based image representation learning

Renata Khasanova

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 ...

EPFL2019

Consistency of Cheeger and Ratio Graph Cuts

Xavier Bresson

This paper establishes the consistency of a family of graph-cut-based algorithms for clustering of data clouds. We consider point clouds obtained as samples of a ground-truth measure. We investigate approaches to clustering based on minimizing objective fu ...

Microtome Publ2016

Segmentation of Developing Human Embryo in Time-lapse Microscopy

Mathieu Salzmann

Being able to efficiently segment a developing embryo from background clutter constitutes an important step in automated monitoring of human embryonic cells. State-of-the-art automatic segmentation methods remain ill-suited to handle the complex behavior a ...

IEEE2016

Downsampling of Signals on Graphs Via Maximum Spanning Trees

Quy Ha Nguyen, Minh Do

Downsampling of signals living on a general weighted graph is not as trivial as of regular signals where we can simply keep every other samples. In this paper we propose a simple, yet effective downsampling scheme in which the underlying graph is approxima ...

Ieee-Inst Electrical Electronics Engineers Inc2015

Hierarchical 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

Fast Partitioning of Vector-Valued Images

Martin Kurt Storath

We propose a fast splitting approach to the classical variational formulation of the image partitioning problem, which is frequently referred to as the Potts or piecewise constant Mumford-Shah model. For vector-valued images, our approach is significantly ...

Siam Publications2014

Applications of a New Separator Theorem for String Graphs

János Pach

An intersection graph of curves in the plane is called a string graph. Matousek almost completely settled a conjecture of the authors by showing that every string graph with m edges admits a vertex separator of size O(root m log m). In the present note, th ...

Cambridge University Press2014