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ICML
2007
IEEE
14 years 8 months ago
Linear and nonlinear generative probabilistic class models for shape contours
We introduce a robust probabilistic approach to modeling shape contours based on a lowdimensional, nonlinear latent variable model. In contrast to existing techniques that use obj...
Graham McNeill, Sethu Vijayakumar
DEXA
2011
Springer
234views Database» more  DEXA 2011»
12 years 7 months ago
Learning Top-k Transformation Rules
Record linkage identifies multiple records referring to the same entity even if they are not bit-wise identical. It is thus an essential technology for data integration and data c...
Sunanda Patro, Wei Wang
KDD
1998
ACM
101views Data Mining» more  KDD 1998»
13 years 11 months ago
Probabilistic Modeling for Information Retrieval with Unsupervised Training Data
We apply a well-known Bayesian probabilistic model to textual information retrieval: the classification of documents based on their relevance to a query. This model was previously...
Ernest P. Chan, Santiago Garcia, Salim Roukos
SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
13 years 8 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
IJCAT
2010
93views more  IJCAT 2010»
13 years 6 months ago
FAETON: Form Analysis and Extraction Tool for ONtology construction
Abstract: This paper presents a method for semi-automatically building tailored application ontologies from a set of data acquisition forms. Such ontologies are intended to facilit...
Rafael Berlanga Llavori, Ernesto Jiménez-Ru...