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NIPS
2003
13 years 11 months ago
Locality Preserving Projections
Many problems in information processing involve some form of dimensionality reduction. In this paper, we introduce Locality Preserving Projections (LPP). These are linear projecti...
Xiaofei He, Partha Niyogi
PAKDD
2010
ACM
173views Data Mining» more  PAKDD 2010»
13 years 7 months ago
Distributed Knowledge Discovery with Non Linear Dimensionality Reduction
Data mining tasks results are usually improved by reducing the dimensionality of data. This improvement however is achieved harder in the case that data lay on a non linear manifol...
Panagis Magdalinos, Michalis Vazirgiannis, Dialect...
ICPR
2006
IEEE
14 years 10 months ago
Scalable Representative Instance Selection and Ranking
Finding a small set of representative instances for large datasets can bring various benefits to data mining practitioners so they can (1) build a learner superior to the one cons...
Xindong Wu, Xingquan Zhu
NAACL
2007
13 years 11 months ago
An Information Retrieval Approach to Sense Ranking
In word sense disambiguation, choosing the most frequent sense for an ambiguous word is a powerful heuristic. However, its usefulness is restricted by the availability of sense-an...
Mirella Lapata, Frank Keller
ICML
2010
IEEE
13 years 10 months ago
Metric Learning to Rank
We study metric learning as a problem of information retrieval. We present a general metric learning algorithm, based on the structural SVM framework, to learn a metric such that ...
Brian McFee, Gert R. G. Lanckriet