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ICDM
2007
IEEE
116views Data Mining» more  ICDM 2007»
15 years 8 months ago
Privacy-Preserving k-NN for Small and Large Data Sets
It is not surprising that there is strong interest in kNN queries to enable clustering, classification and outlierdetection tasks. However, previous approaches to privacypreservi...
Artak Amirbekyan, Vladimir Estivill-Castro
CVPR
2012
IEEE
13 years 4 months ago
Scalable k-NN graph construction for visual descriptors
The k-NN graph has played a central role in increasingly popular data-driven techniques for various learning and vision tasks; yet, finding an efficient and effective way to con...
Jing Wang, Jingdong Wang, Gang Zeng, Zhuowen Tu, R...
COLOGNETWENTE
2010
14 years 10 months ago
A Branch-and-price Approach to the k-Clustering Minimum Biclique Completion Problem
Given a bipartite graph G = (S, T, E), we consider the problem of finding k bipartite subgraphs, called "clusters", such that each vertex i of S appears in exactly one o...
Stefano Gualandi, Francesco Maffioli, Claudio Magn...
ESA
2004
Springer
128views Algorithms» more  ESA 2004»
15 years 7 months ago
Incremental Algorithms for Facility Location and k-Median
In the incremental versions of Facility Location and k-Median, the demand points arrive one at a time and the algorithm must maintain a good solution by either adding each new dema...
Dimitris Fotakis
ECML
2003
Springer
15 years 7 months ago
Robust k-DNF Learning via Inductive Belief Merging
A central issue in logical concept induction is the prospect of inconsistency. This problem may arise due to noise in the training data, or because the target concept does not fit...
Frédéric Koriche, Joël Quinquet...