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» Improved Sparse Bump Modeling for Electrophysiological Data
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BMCBI
2007
215views more  BMCBI 2007»
13 years 7 months ago
Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregres
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
Rainer Opgen-Rhein, Korbinian Strimmer
NLPRS
2001
Springer
13 years 12 months ago
A Probabilistic Model for Japanese Zero Pronoun Resolution Integrating Syntactic and Semantic Features
This paper proposes a method to resolve Japanese zero pronouns by identifying their antecedents. Our method uses a probabilistic model, which is decomposed into syntactic and sema...
Kazuhiro Seki, Atsushi Fujii, Tetsuya Ishikawa
KDD
2008
ACM
176views Data Mining» more  KDD 2008»
14 years 7 months ago
Context-aware query suggestion by mining click-through and session data
Query suggestion plays an important role in improving the usability of search engines. Although some recently proposed methods can make meaningful query suggestions by mining quer...
Huanhuan Cao, Daxin Jiang, Jian Pei, Qi He, Zhen L...
CIKM
2010
Springer
13 years 6 months ago
Decomposing background topics from keywords by principal component pursuit
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
Kerui Min, Zhengdong Zhang, John Wright, Yi Ma
NIPS
2008
13 years 8 months ago
Designing neurophysiology experiments to optimally constrain receptive field models along parametric submanifolds
Sequential optimal design methods hold great promise for improving the efficiency of neurophysiology experiments. However, previous methods for optimal experimental design have in...
Jeremy Lewi, Robert J. Butera, David M. Schneider,...