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BMCBI
2007
215views more  BMCBI 2007»
15 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
TECS
2008
122views more  TECS 2008»
15 years 7 months ago
Quantitative analysis of the speed/accuracy trade-off in transaction level modeling
tion. Transaction Level Modeling (TLM) has been proposed to abstract communication for highspeed system simulation and rapid design space exploration. Although being widely accepte...
Gunar Schirner, Rainer Dömer
CVPR
2004
IEEE
16 years 9 months ago
Multiple Bernoulli Relevance Models for Image and Video Annotation
Retrieving images in response to textual queries requires some knowledge of the semantics of the picture. Here, we show how we can do both automatic image annotation and retrieval...
Shaolei Feng, Raghavan Manmatha, Victor Lavrenko
ECCV
2006
Springer
16 years 9 months ago
Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition
Abstract. In this paper we investigate a new method of learning partbased models for visual object recognition, from training data that only provides information about class member...
David J. Crandall, Daniel P. Huttenlocher
SIGSOFT
2007
ACM
16 years 7 months ago
Quantitative verification: models techniques and tools
Automated verification is a technique for establishing if certain properties, usually expressed in temporal logic, hold for a system model. The model can be defined using a high-l...
Marta Z. Kwiatkowska