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DAGSTUHL
2006
13 years 9 months ago
How fast does the stationary distribution of the Markov chain modelling EAs concentrate on the homogeneous populations for small
One of the main difficulties faced when analyzing Markov chains modelling evolutionary algorithms is that their cardinality grows quite fast. A reasonable way to deal with this iss...
Boris Mitavskiy, Jonathan E. Rowe
TKDE
2008
171views more  TKDE 2008»
13 years 7 months ago
Efficient Similarity Search in Nonmetric Spaces with Local Constant Embedding
Similarity-based search has been a key factor for many applications such as multimedia retrieval, data mining, Web search and retrieval, and so on. There are two important issues r...
Lei Chen 0002, Xiang Lian
CORR
2012
Springer
230views Education» more  CORR 2012»
12 years 3 months ago
Fast Triangle Counting through Wedge Sampling
Graphs and networks are used to model interactions in a variety of contexts, and there is a growing need to be able to quickly assess the qualities of a graph in order to understa...
C. Seshadhri, Ali Pinar, Tamara G. Kolda
ICCV
2005
IEEE
14 years 1 months ago
Learning Models for Predicting Recognition Performance
This paper addresses one of the fundamental problems encountered in performance prediction for object recognition. In particular we address the problems related to estimation of s...
Rong Wang, Bir Bhanu
WAOA
2007
Springer
158views Algorithms» more  WAOA 2007»
14 years 1 months ago
Deterministic Algorithms for Rank Aggregation and Other Ranking and Clustering Problems
We consider ranking and clustering problems related to the aggregation of inconsistent information. Ailon, Charikar, and Newman [1] proposed randomized constant factor approximatio...
Anke van Zuylen, David P. Williamson