93 search results - page 15 / 19 » Greedy Kernel Principal Component Analysis |
SIGIR
2008
ACM
13 years 9 months ago
2008
ACM
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
ICML
2009
IEEE
14 years 10 months ago
2009
IEEE
Training principles for unsupervised learning are often derived from motivations that appear to be independent of supervised learning. In this paper we present a simple unificatio...
NIPS
2003
13 years 11 months ago
2003
In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...
IJON
2007
13 years 9 months ago
2007
Kernel principal component analysis (KPCA) extracts features of samples with an efficiency in inverse proportion to the size of the training sample set. In this paper, we develop...
ICDAR
2009
IEEE
13 years 7 months ago
2009
IEEE
We report an automatic feature discovery method that achieves results comparable to a manually chosen, larger feature set on a document image content extraction problem: the locat...