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» Making Distributed Applications Robust
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KDD
2012
ACM
207views Data Mining» more  KDD 2012»
13 years 2 months ago
Robust multi-task feature learning
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
Pinghua Gong, Jieping Ye, Changshui Zhang
127
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ICUMT
2009
14 years 9 months ago
A scalable based multicast model for P2P Conferencing applications
Multicast conferencing is a rapidly-growing area of Internet use. Audio, video and other media such as shared whiteboard data can be distributed efficiently between groups of confe...
Mourad Amad, Zahir Haddad, Lachemi Khenous, Kamal ...
ICCV
2007
IEEE
16 years 1 months ago
Variational Segmentation using Fuzzy Region Competition and Local Non-Parametric Probability Density Functions
We describe a novel variational segmentation algorithm designed to split an image in two regions based on their intensity distributions. A functional is proposed to integrate the ...
Benoit Mory, Roberto Ardon, Jean-Philippe Thiran
SOSP
2009
ACM
15 years 8 months ago
Upright cluster services
The UpRight library seeks to make Byzantine fault tolerance (BFT) a simple and viable alternative to crash fault tolerance for a range of cluster services. We demonstrate UpRight ...
Allen Clement, Manos Kapritsos, Sangmin Lee, Yang ...
ICRA
2009
IEEE
185views Robotics» more  ICRA 2009»
15 years 6 months ago
Ad-hoc wireless network coverage with networked robots that cannot localize
— We study a fully distributed, reactive algorithm for deployment and maintenance of a mobile communication backbone that provides an area around a network gateway with wireless ...
Nikolaus Correll, Jonathan Bachrach, Daniel Vicker...