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» The Frobenius Problem and Its Generalizations
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ICML
2009
IEEE
16 years 7 months ago
Multi-assignment clustering for Boolean data
Conventional clustering methods typically assume that each data item belongs to a single cluster. This assumption does not hold in general. In order to overcome this limitation, w...
Andreas P. Streich, Mario Frank, David A. Basin, J...
KDD
2006
ACM
166views Data Mining» more  KDD 2006»
16 years 7 months ago
Anonymizing sequential releases
An organization makes a new release as new information become available, releases a tailored view for each data request, releases sensitive information and identifying information...
Ke Wang, Benjamin C. M. Fung
STOC
2006
ACM
244views Algorithms» more  STOC 2006»
16 years 7 months ago
Approximate nearest neighbors and the fast Johnson-Lindenstrauss transform
We introduce a new low-distortion embedding of d 2 into O(log n) p (p = 1, 2), called the Fast-Johnson-LindenstraussTransform. The FJLT is faster than standard random projections ...
Nir Ailon, Bernard Chazelle
SIGMOD
2009
ACM
134views Database» more  SIGMOD 2009»
16 years 6 months ago
Keyword query cleaning using hidden Markov models
In this paper, we consider the problem of keyword query cleaning for structured databases from a probabilistic approach. Keyword query cleaning consists of rewriting the user quer...
Ken Q. Pu
PAKDD
2009
ACM
209views Data Mining» more  PAKDD 2009»
16 years 3 months ago
Approximate Spectral Clustering.
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...