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» The number of guillotine partitions in d dimensions
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ICASSP
2011
IEEE
13 years 15 days ago
Co-clustering as multilinear decomposition with sparse latent factors
The K-means clustering problem seeks to partition the columns of a data matrix in subsets, such that columns in the same subset are ‘close’ to each other. The co-clustering pr...
Evangelos E. Papalexakis, Nicholas D. Sidiropoulos
ESWS
2008
Springer
13 years 10 months ago
Conceptual Clustering and Its Application to Concept Drift and Novelty Detection
Abstract. The paper presents a clustering method which can be applied to populated ontologies for discovering interesting groupings of resources therein. The method exploits a simp...
Nicola Fanizzi, Claudia d'Amato, Floriana Esposito
COMPGEOM
1994
ACM
14 years 26 days ago
Query-Sensitive Ray Shooting
Ray (segment) shooting is the problem of determining the first intersection between a ray (directed line segment) and a collection of polygonal or polyhedral obstacles. In order t...
Joseph S. B. Mitchell, David M. Mount, Subhash Sur...
SODA
2010
ACM
202views Algorithms» more  SODA 2010»
14 years 6 months ago
Counting Inversions, Offline Orthogonal Range Counting, and Related Problems
We give an O(n lg n)-time algorithm for counting the number of inversions in a permutation on n elements. This improves a long-standing previous bound of O(n lg n/ lg lg n) that ...
Timothy M. Chan, Mihai Patrascu
COMPGEOM
2009
ACM
14 years 1 months ago
k-means requires exponentially many iterations even in the plane
The k-means algorithm is a well-known method for partitioning n points that lie in the d-dimensional space into k clusters. Its main features are simplicity and speed in practice....
Andrea Vattani