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» Algorithms for discovering bucket orders from data
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KDD
2001
ACM
253views Data Mining» more  KDD 2001»
16 years 4 months ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Jens-Peter Dittrich, Bernhard Seeger
KDD
2012
ACM
190views Data Mining» more  KDD 2012»
13 years 6 months ago
Multi-label hypothesis reuse
Multi-label learning arises in many real-world tasks where an object is naturally associated with multiple concepts. It is well-accepted that, in order to achieve a good performan...
Sheng-Jun Huang, Yang Yu, Zhi-Hua Zhou
JIB
2007
88views more  JIB 2007»
15 years 4 months ago
Achieving k-anonymity in DataMarts used for gene expressions exploitation
Gene expression profiling is a sophisticated method to discover differences in activation patterns of genes between different patient collectives. By reasonably defining patient...
Konrad Stark, Johann Eder, Kurt Zatloukal
121
Voted
RECOMB
2010
Springer
15 years 6 months ago
An Algorithmic Framework for Predicting Side-Effects of Drugs
Abstract. One of the critical stages in drug development is the identification of potential side effects for promising drug leads. Large scale clinical experiments aimed at discove...
Nir Atias, Roded Sharan
131
Voted
EDBT
2010
ACM
185views Database» more  EDBT 2010»
15 years 11 months ago
Optimizing joins in a map-reduce environment
Implementations of map-reduce are being used to perform many operations on very large data. We examine strategies for joining several relations in the map-reduce environment. Our ...
Foto N. Afrati, Jeffrey D. Ullman