Publications associées à Line graph

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Everything You Always Wanted to Know about Multicore Graph Processing but Were Afraid to Ask

Willy Zwaenepoel, Baptiste Joseph Eustache Lepers, Jasmina Malicevic

Graph processing systems are used in a wide variety of fields, ranging from biology to social networks, and a large number of such systems have been described in the recent literature. We perform a systematic comparison of various techniques proposed to sp ...

USENIX Association2017

Stationary signal processing on graphs

Pierre Vandergheynst, Nathanaël Perraudin

Graphs are a central tool in machine learning and information processing as they allow to conveniently capture the structure of complex datasets. In this context, it is of high importance to develop flexible models of signals defined over graphs or network ...

Institute of Electrical and Electronics Engineers2017

Spinner: Scalable Graph Partitioning in the Cloud

Andreas Loukas, Dionysios Logothetis

In this paper, we present a graph partitioning algorithm to partition graphs with trillions of edges. To achieve such scale, our solution leverages the vertex-centric Pregel abstraction provided by Giraph, a system for large-scale graph analytics. We desig ...

Ieee2017

Diverse M-Best Solutions by Dynamic Programming

Michaël Unser, Virginie Sophie Uhlmann

Many computer vision pipelines involve dynamic programming primitives such as finding a shortest path or the minimum energy solution in a tree-shaped probabilistic graphical model. In such cases, extracting not merely the best, but the set of M-best soluti ...

Springer2017

Lower Bounds on Active Learning for Graphical Model Selection

Volkan Cevher, Jonathan Mark Scarlett

We consider the problem of estimating the underlying graph associated with a Markov random field, with the added twist that the decoding algorithm can iteratively choose which subsets of nodes to sample based on the previous samples, resulting in an active ...

2017

Coordination of Dynamic Software Components with JavaBIP

Simon Bliudze, Anastasia Mavridou

JavaBIP allows the coordination of software components by clearly separating the functional and coordination aspects of the system behavior. JavaBIP implements the principles of the BIP component framework rooted in rigorous operational semantics. Recent w ...

Springer International Publishing2017

Graph learning under sparsity priors

Pascal Frossard, Hermina Petric Maretic

Graph signals offer a very generic and natural representation for data that lives on networks or irregular structures. The actual data structure is however often unknown a priori but can sometimes be estimated from the knowledge of the application domain. ...

Ieee2017

Filtering Random Graph Processes Over Random Time-Varying Graphs

Andreas Loukas

Graph filters play a key role in processing the graph spectra of signals supported on the vertices of a graph. However, despite their widespread use, graph filters have been analyzed only in the deterministic setting, ignoring the impact of stochasticity i ...

Institute of Electrical and Electronics Engineers2017

Line graph

Graph Chatbot

Chattez avec Graph Search

Everything You Always Wanted to Know about Multicore Graph Processing but Were Afraid to Ask

Stationary signal processing on graphs

Graph-Based Classification of Omnidirectional Images

Spinner: Scalable Graph Partitioning in the Cloud

Diverse M-Best Solutions by Dynamic Programming

Lower Bounds on Active Learning for Graphical Model Selection

Coordination of Dynamic Software Components with JavaBIP

Graph learning under sparsity priors

Filtering Random Graph Processes Over Random Time-Varying Graphs

Exploring Selection Bias by Causal Frailty Models

Lower Bounds on Active Learning for Graphical Model Selection

Coordination of Dynamic Software Components with JavaBIP

Graph learning under sparsity priors

Filtering Random Graph Processes Over Random Time-Varying Graphs

Exploring Selection Bias by Causal Frailty Models

Everything You Always Wanted to Know about Multicore Graph Processing but Were Afraid to Ask

Graph-Based Classification of Omnidirectional Images

Spinner: Scalable Graph Partitioning in the Cloud

Diverse M-Best Solutions by Dynamic Programming

Stationary signal processing on graphs