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RECOMB
2004
Springer
16 years 4 months ago
Learning Regulatory Network Models that Represent Regulator States and Roles
Abstract. We present an approach to inferring probabilistic models of generegulatory networks that is intended to provide a more mechanistic representation of transcriptional regul...
Keith Noto, Mark Craven
ACL
2007
15 years 5 months ago
Guiding Semi-Supervision with Constraint-Driven Learning
Over the last few years, two of the main research directions in machine learning of natural language processing have been the study of semi-supervised learning algorithms as a way...
Ming-Wei Chang, Lev-Arie Ratinov, Dan Roth
BMCBI
2007
215views more  BMCBI 2007»
15 years 4 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
COLING
2010
14 years 11 months ago
Cross-Market Model Adaptation with Pairwise Preference Data for Web Search Ranking
Machine-learned ranking techniques automatically learn a complex document ranking function given training data. These techniques have demonstrated the effectiveness and flexibilit...
Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, ...
EMNLP
2007
15 years 5 months ago
A Discriminative Learning Model for Coordinate Conjunctions
We propose a sequence-alignment based method for detecting and disambiguating coordinate conjunctions. In this method, averaged perceptron learning is used to adapt the substituti...
Masashi Shimbo, Kazuo Hara