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CORR
2008
Springer
13 years 7 months ago
2008
Springer
One of the most fundamental problems in large-scale network analysis is to determine the importance of a particular node in a network. Betweenness centrality is the most widely us...
MP
2006
13 years 7 months ago
2006
There are many applications related to singly linearly constrained quadratic programs subjected to upper and lower bounds. In this paper, a new algorithm based on secant approximat...
APPROX
2010
Springer
13 years 9 months ago
2010
Springer
A recurring theme in the literature on derandomization is that probabilistic algorithms can be simulated quickly by deterministic algorithms, if one can obtain impressive (i.e., s...
ICDM
2006
IEEE
14 years 1 months ago
2006
IEEE
The k-means algorithm is a popular clustering method used in many different fields of computer science, such as data mining, machine learning and information retrieval. However, ...
COLT
2006
Springer
13 years 11 months ago
2006
Springer
We describe a new approach for understanding the difficulty of designing efficient learning algorithms. We prove that the existence of an efficient learning algorithm for a circui...