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» Robust Feature Selection Algorithms
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101
Voted
KDD
2006
ACM
150views Data Mining» more  KDD 2006»
16 years 2 months ago
Maximally informative k-itemsets and their efficient discovery
In this paper we present a new approach to mining binary data. We treat each binary feature (item) as a means of distinguishing two sets of examples. Our interest is in selecting ...
Arno J. Knobbe, Eric K. Y. Ho
ICML
2009
IEEE
16 years 3 months ago
More generality in efficient multiple kernel learning
Recent advances in Multiple Kernel Learning (MKL) have positioned it as an attractive tool for tackling many supervised learning tasks. The development of efficient gradient desce...
Manik Varma, Bodla Rakesh Babu
110
Voted
ICML
2008
IEEE
16 years 3 months ago
Expectation-maximization for sparse and non-negative PCA
We study the problem of finding the dominant eigenvector of the sample covariance matrix, under additional constraints on the vector: a cardinality constraint limits the number of...
Christian D. Sigg, Joachim M. Buhmann
KDD
2002
ACM
186views Data Mining» more  KDD 2002»
16 years 2 months ago
Topic-conditioned novelty detection
Automated detection of the first document reporting each new event in temporally-sequenced streams of documents is an open challenge. In this paper we propose a new approach which...
Yiming Yang, Jian Zhang, Jaime G. Carbonell, Chun ...
144
Voted
JAIR
2010
94views more  JAIR 2010»
15 years 28 days ago
Which Clustering Do You Want? Inducing Your Ideal Clustering with Minimal Feedback
While traditional research on text clustering has largely focused on grouping documents by topic, it is conceivable that a user may want to cluster documents along other dimension...
Sajib Dasgupta, Vincent Ng