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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
ICDM
2010
IEEE
273views Data Mining» more  ICDM 2010»
13 years 5 months ago
Learning Maximum Lag for Grouped Graphical Granger Models
Temporal causal modeling has been a highly active research area in the last few decades. Temporal or time series data arises in a wide array of application domains ranging from med...
Amit Dhurandhar
SIAMJO
2002
87views more  SIAMJO 2002»
13 years 7 months ago
An Optimization Approach for Radiosurgery Treatment Planning
We outline a new approach for radiosurgery treatment planning, based on solving a series of optimization problems. We consider a specific treatment planning problem for a speciali...
Michael C. Ferris, Jinho Lim, David M. Shepard
WSDM
2012
ACM
301views Data Mining» more  WSDM 2012»
12 years 3 months ago
Learning evolving and emerging topics in social media: a dynamic nmf approach with temporal regularization
As massive repositories of real-time human commentary, social media platforms have arguably evolved far beyond passive facilitation of online social interactions. Rapid analysis o...
Ankan Saha, Vikas Sindhwani
MICCAI
2005
Springer
14 years 8 months ago
A Prediction Framework for Cardiac Resynchronization Therapy Via 4D Cardiac Motion Analysis
Abstract. We propose a novel framework to predict pacing sites in the left ventricle (LV) of a heart and its result can be used to assist pacemaker implantation and programming in ...
Heng Huang, Li Shen, Rong Zhang, Fillia Makedon, B...