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CVPR
2005
IEEE
16 years 7 months ago
WaldBoost - Learning for Time Constrained Sequential Detection
: In many computer vision classification problems, both the error and time characterizes the quality of a decision. We show that such problems can be formalized in the framework of...
Jan Sochman, Jiri Matas
167
Voted
SIMVIS
2004
15 years 6 months ago
3D Shape Matching Using Skeleton Graphs
We describe a method to match 3D polygonal geometry models using their internal skeleton graphs. These graphs carry information about the overall shape of the model. In order to m...
Angela Brennecke, Tobias Isenberg
NIPS
2007
15 years 6 months ago
Boosting Algorithms for Maximizing the Soft Margin
We present a novel boosting algorithm, called SoftBoost, designed for sets of binary labeled examples that are not necessarily separable by convex combinations of base hypotheses....
Manfred K. Warmuth, Karen A. Glocer, Gunnar Rä...
142
Voted
ML
2006
ACM
142views Machine Learning» more  ML 2006»
15 years 5 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
INFOCOM
2009
IEEE
15 years 11 months ago
MARA: Maximum Alternative Routing Algorithm
—In hop-by-hop networks, provision of multipath routes for all nodes can improve fault tolerance and performance. In this paper we study the multipath route calculation by constr...
Yasuhiro Ohara, Shinji Imahori, Rodney Van Meter