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» Learning Models for Multi-Source Integration
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AROBOTS
2011
14 years 6 months ago
Learning GP-BayesFilters via Gaussian process latent variable models
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
Jonathan Ko, Dieter Fox
ICDM
2003
IEEE
136views Data Mining» more  ICDM 2003»
15 years 5 months ago
Statistical Relational Learning for Document Mining
A major obstacle to fully integrated deployment of many data mining algorithms is the assumption that data sits in a single table, even though most real-world databases have compl...
Alexandrin Popescul, Lyle H. Ungar, Steve Lawrence...
AAAI
2000
15 years 1 months ago
Integrating Equivalency Reasoning into Davis-Putnam Procedure
Equivalency clauses (Xors or modulo 2 arithmetics) represent a common structure in the SAT-encoding of many hard real-world problems and constitute a major obstacle to DavisPutnam...
Chu Min Li
KDD
2004
ACM
237views Data Mining» more  KDD 2004»
16 years 5 days ago
Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
Mario Medvedovic, Junhai Guo
NN
2008
Springer
169views Neural Networks» more  NN 2008»
14 years 11 months ago
Modeling a flexible representation machinery of human concept learning
dely acknowledged that categorically organized abstract knowledge plays a significant role in high-order human cognition. Yet, there are many unknown issues about the nature of ho...
Toshihiko Matsuka, Yasuaki Sakamoto, Arieta Chouch...