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PAMI
2006
127views more  PAMI 2006»
15 years 2 months ago
Incremental Nonlinear Dimensionality Reduction by Manifold Learning
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
Martin H. C. Law, Anil K. Jain
EUC
2005
Springer
15 years 7 months ago
Middleware Architecture for Context Knowledge Discovery in Ubiquitous Computing
Advanced analysis of data for extracting useful knowledge is the next natural step in the world of ubiquitous computing. So far, most of the ubiquitous systems process knowledge in...
Kim Anh Pham Ngoc, Young-Koo Lee, Sungyoung Lee
KDD
2012
ACM
201views Data Mining» more  KDD 2012»
13 years 4 months ago
Learning from crowds in the presence of schools of thought
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
Yuandong Tian, Jun Zhu
ECCB
2003
IEEE
15 years 7 months ago
Gene networks inference using dynamic Bayesian networks
This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactio...
Bruno-Edouard Perrin, Liva Ralaivola, Aurél...
189
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VLDB
2003
ACM
165views Database» more  VLDB 2003»
16 years 2 months ago
Learning to match ontologies on the Semantic Web
On the Semantic Web, data will inevitably come from many different ontologies, and information processing across ontologies is not possible without knowing the semantic mappings be...
AnHai Doan, Jayant Madhavan, Robin Dhamankar, Pedr...