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» Reconstruction for Models on Random Graphs
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ICML
2004
IEEE
15 years 5 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
COR
2006
94views more  COR 2006»
14 years 12 months ago
A comparison of two different formulations for arc routing problems on mixed graphs
Arc Routing Problems on mixed graphs have been modelled in the literature either using just one variable per edge or associating to each edge two variables, each one representing ...
Angel Corberán, Enrique Mota, José M...
CORR
2006
Springer
119views Education» more  CORR 2006»
14 years 12 months ago
Network Inference from Co-Occurrences
The study of networked systems is an emerging field, impacting almost every area of engineering and science, including the important domains of communication systems, biology, soc...
Michael Rabbat, Mário A. T. Figueiredo, Rob...
SAC
2002
ACM
14 years 11 months ago
A mobility and traffic generation framework for modeling and simulating ad hoc communication networks
We present a generic mobility and traffic generation framework that can be incorporated into a tool for modeling and simulating large scale ad hoc networks. Three components of thi...
Christopher L. Barrett, Madhav V. Marathe, James P...
WAW
2007
Springer
157views Algorithms» more  WAW 2007»
15 years 6 months ago
Stochastic Kronecker Graphs
A random graph model based on Kronecker products of probability matrices has been recently proposed as a generative model for large-scale real-world networks such as the web. This...
Mohammad Mahdian, Ying Xu 0002