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A tutorial on graph models for scheduling round-robin sports tournaments

Related publications (32)

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Graph Signal Processing

Ntorina Thanou

Over the past few decades we have been experiencing an explosion of information generated by large networks of sensors and other data sources. Much of this data is intrinsically structured, such as traffic evolution in a transportation network, temperature ...

EPFL2016

From data to structures

Vasilis Kalofolias

Weighted undirected graphs are a simple, yet powerful way to encode structure in data. A first question we need to address regarding such graphs is how to use them effectively to enhance machine learning problems. A second but more important question is ho ...

EPFL2016

Chaos: Scale-out Graph Processing from Secondary Storage

Willy Zwaenepoel, Laurent Bindschaedler, Amitabha Roy, Jasmina Malicevic

Chaos scales graph processing from secondary storage to multiple machines in a cluster. Earlier systems that process graphs from secondary storage are restricted to a single ma- chine, and therefore limited by the bandwidth and capacity of the storage syst ...

2015

Scale-up Graph Processing in the Cloud: Challenges and Solutions

Willy Zwaenepoel, Amitabha Roy, Jasmina Malicevic

Processing large graphs is an important part of the big-data problem. Recently a number of scale-up systems such as X-Stream, Graphchi and Turbograph have been proposed for processing large graphs using secondary storage on a single machine. The design and ...

Graph-based representation and coding of multiview geometry

Pascal Frossard, Thomas Maugey

We propose a new approach for describing the geometry information of multiview image representations. Rather than transmitting the raw geometry of the scene, under the form of depth information, we build a graph that represents the connections between corr ...

2013

X-Stream: Edge-centric Graph Processing using Streaming Partitions

Willy Zwaenepoel, Amitabha Roy, Ivo Mihailovic

X-Stream is a system for processing both in-memory and out-of-core graphs on a single shared-memory machine. While retaining the scatter-gather programming model with state stored in the vertices, X-Stream is novel in (i) using an edge-centric rather than ...

ACM2013

Graph-Based Information Processing

Amin Karbasi

We live in a world characterized by massive information transfer and real-time communication. The demand for efficient yet low-complexity algorithms is widespread across different fields, including machine learning, signal processing and communications. Mo ...

EPFL2012

Robust Duplicate Detection of 2D and 3D Objects

Touradj Ebrahimi, Jong Seok Lee, Lutz Goldmann, Ivan Ivanov, Péter Vajda

In this paper, we analyze our graph-based approach for 2D and 3D object duplicate detection in still images. A graph model is used to represent the 3D spatial information of the object based on the features extracted from training images so that an explici ...

2010

Graph-Constrained Group Testing

Amin Karbasi, Mahdi Cheraghchi Bashi Astaneh, Soheil Mohajerzefreh

Non-adaptive group testing involves grouping arbitrary subsets of

n

items into different pools and identifying defective items based on tests obtained for each pool. Motivated by applications in network tomography, sensor networks and infection propagati ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Graph-Based Approach for 3D Object Duplicate Detection

Touradj Ebrahimi, Frédéric Dufaux, Péter Vajda

In this paper, we consider the challenging problem of object duplicate detection and localization. Several applications require efficient object duplicate detection methods, such as automatic video and image tagging, video surveillance, and high level imag ...

2009

Graph-Constrained Group Testing

Amin Karbasi, Mahdi Cheraghchi Bashi Astaneh, Soheil Mohajerzefreh

Non-adaptive group testing involves grouping arbitrary subsets of

n

items into different pools and identifying defective items based on tests obtained for each pool. Motivated by applications in network tomography, sensor networks and infection propagati ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010