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» Set cover algorithms for very large datasets
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JMLR
2012
13 years 7 days ago
Marginal Regression For Multitask Learning
Variable selection is an important and practical problem that arises in analysis of many high-dimensional datasets. Convex optimization procedures that arise from relaxing the NP-...
Mladen Kolar, Han Liu
CINQ
2004
Springer
125views Database» more  CINQ 2004»
15 years 3 months ago
Deducing Bounds on the Support of Itemsets
Mining Frequent Itemsets is the core operation of many data mining algorithms. This operation however, is very data intensive and sometimes produces a prohibitively large output. I...
Toon Calders
ICMLA
2010
14 years 7 months ago
Boosting Multi-Task Weak Learners with Applications to Textual and Social Data
Abstract--Learning multiple related tasks from data simultaneously can improve predictive performance relative to learning these tasks independently. In this paper we propose a nov...
Jean Baptiste Faddoul, Boris Chidlovskii, Fabien T...
VLDB
1999
ACM
224views Database» more  VLDB 1999»
15 years 2 months ago
Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering
Many applications require the clustering of large amounts of high-dimensional data. Most clustering algorithms, however, do not work e ectively and e ciently in highdimensional sp...
Alexander Hinneburg, Daniel A. Keim
SIGMOD
2004
ACM
199views Database» more  SIGMOD 2004»
15 years 10 months ago
Approximate XML Query Answers
The rapid adoption of XML as the standard for data representation and exchange foreshadows a massive increase in the amounts of XML data collected, maintained, and queried over th...
Neoklis Polyzotis, Minos N. Garofalakis, Yannis E....