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» Random Spanning Trees and the Prediction of Weighted Graphs
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ICML
2004
IEEE
14 years 1 months ago
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
Hisashi Kashima, Yuta Tsuboi
ISMB
1993
13 years 9 months ago
Computationally Efficient Cluster Representation in Molecular Sequence Megaclassification
Molecular sequence megaclassification is a technique for automated protein sequence analysis and annotation. Implementation of the method has been limited by the need to store and...
David J. States, Nomi L. Harris, Lawrence Hunter
JOIN
2007
91views more  JOIN 2007»
13 years 7 months ago
An Optimal Rebuilding Strategy for an Incremental Tree Problem
This paper is devoted to the following incremental problem. Initially, a graph and a distinguished subset of vertices, called initial group, are given. This group is connected by ...
Nicolas Thibault, Christian Laforest
ESA
2009
Springer
109views Algorithms» more  ESA 2009»
14 years 2 months ago
Iterative Rounding for Multi-Objective Optimization Problems
In this paper we show that iterative rounding is a powerful and flexible tool in the design of approximation algorithms for multiobjective optimization problems. We illustrate tha...
Fabrizio Grandoni, R. Ravi, Mohit Singh
DIALM
2008
ACM
135views Algorithms» more  DIALM 2008»
13 years 9 months ago
Symmetric range assignment with disjoint MST constraints
If V is a set of n points in the unit square [0, 1]2 , and if R : V + is an assignment of positive real numbers (radii) to to those points, define a graph G(R) as follows: {v, w}...
Eric Schmutz