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123
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IJHIS
2006
104views more  IJHIS 2006»
15 years 17 days ago
Incremental evolution strategy for function optimization
This paper presents a novel evolutionary approach for function optimization Incremental Evolution Strategy (IES). Two strategies are proposed. One is to evolve the input variables...
Sheng Uei Guan, Wenting Mo
AAAI
2008
15 years 2 months ago
Lifted Probabilistic Inference with Counting Formulas
Lifted inference algorithms exploit repeated structure in probabilistic models to answer queries efficiently. Previous work such as de Salvo Braz et al.'s first-order variabl...
Brian Milch, Luke S. Zettlemoyer, Kristian Kerstin...
CORR
2012
Springer
184views Education» more  CORR 2012»
13 years 8 months ago
Noisy-OR Models with Latent Confounding
Given a set of experiments in which varying subsets of observed variables are subject to intervention, we consider the problem of identifiability of causal models exhibiting late...
Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoy...
142
Voted
IJDMB
2008
132views more  IJDMB 2008»
15 years 17 days ago
A Bayesian framework for knowledge driven regression model in micro-array data analysis
: This paper addresses the sparse data problem in the linear regression model, namely the number of variables is significantly larger than the number of the data points for regress...
Rong Jin, Luo Si, Christina Chan
ICML
2004
IEEE
15 years 6 months ago
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
Hisashi Kashima, Yuta Tsuboi