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ICA
2010
Springer
13 years 6 months ago
Use of Prior Knowledge in a Non-Gaussian Method for Learning Linear Structural Equation Models
Abstract. We discuss causal structure learning based on linear structural equation models. Conventional learning methods most often assume Gaussianity and create many indistinguish...
Takanori Inazumi, Shohei Shimizu, Takashi Washio
DAC
2004
ACM
14 years 5 months ago
STAC: statistical timing analysis with correlation
Current technology trends have led to the growing impact of both inter-die and intra-die process variations on circuit performance. While it is imperative to model parameter varia...
Jiayong Le, Xin Li, Lawrence T. Pileggi
UAI
2008
13 years 6 months ago
Discovering Cyclic Causal Models by Independent Components Analysis
We generalize Shimizu et al's (2006) ICA-based approach for discovering linear non-Gaussian acyclic (LiNGAM) Structural Equation Models (SEMs) from causally sufficient, conti...
Gustavo Lacerda, Peter Spirtes, Joseph Ramsey, Pat...
ICA
2004
Springer
13 years 10 months ago
Temporal Decorrelation as Preprocessing for Linear and Post-nonlinear ICA
Abstract. We present a straightforward way to use temporal decorrelation as preprocessing in linear and post-nonlinear independent component analysis (ICA) with higher order statis...
Juha Karvanen, Toshihisa Tanaka
DAC
2004
ACM
14 years 5 months ago
Fast statistical timing analysis handling arbitrary delay correlations
CT An efficient statistical timing analysis algorithm that can handle arbitrary (spatial and structural) causes of delay correlation is described. The algorithm derives the entire ...
Michael Orshansky, Arnab Bandyopadhyay