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NIPS
2007
13 years 9 months ago
Semi-Supervised Multitask Learning
A semi-supervised multitask learning (MTL) framework is presented, in which M parameterized semi-supervised classifiers, each associated with one of M partially labeled data mani...
Qiuhua Liu, Xuejun Liao, Lawrence Carin
VMV
2008
165views Visualization» more  VMV 2008»
13 years 9 months ago
Fast Global Labeling for Real-Time Stereo Using Multiple Plane Sweeps
This work presents a real-time, data-parallel approach for global label assignment on regular grids. The labels are selected according to a Markov random field energy with a Potts...
Christopher Zach, David Gallup, Jan-Michael Frahm,...
IJCAI
2003
13 years 9 months ago
Making the Breakout Algorithm Complete Using Systematic Search
Local search algorithms have been very successful for solving constraint satisfaction problems (CSP). However, a major weakness has been that local search is unable to detect unso...
Carlos Eisenberg, Boi Faltings
HICSS
2008
IEEE
153views Biometrics» more  HICSS 2008»
13 years 8 months ago
Fault-Tolerant k-Fold Pivot Routing in Wireless Sensor Networks
Selecting a small set of nodes called pivots, from all the nodes in a network and maintaining the routing infrastructure to and among each other can reduce routing overhead and ex...
Doina Bein
AUTOMATICA
2006
122views more  AUTOMATICA 2006»
13 years 7 months ago
Gibbs sampler-based coordination of autonomous swarms
In this paper a novel, Gibbs sampler-based algorithm is proposed for coordination of autonomous swarms. The swarm is modeled as a Markov random field (MRF) on a graph with a time-...
Wei Xi, Xiaobo Tan, John S. Baras