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JMLR
2010
134views more  JMLR 2010»
14 years 4 months ago
Inference of Graphical Causal Models: Representing the Meaningful Information of Probability Distributions
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
Jan Lemeire, Kris Steenhaut
ISLPED
1997
ACM
114views Hardware» more  ISLPED 1997»
15 years 1 months ago
Cycle-accurate macro-models for RT-level power analysis
 In this paper we present a methodology and techniques for generating cycle-accurate macro-models for RTlevel power analysis. The proposed macro-model predicts not only...
Qinru Qiu, Qing Wu, Massoud Pedram, Chih-Shun Ding
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DAC
2004
ACM
15 years 10 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
TDP
2008
67views more  TDP 2008»
14 years 9 months ago
Generating Sufficiency-based Non-Synthetic Perturbed Data
The mean vector and covariance matrix are sufficient statistics when the un derlying distribution is multivariate normal. Many type of statistical analyses used in practice rely on...
Krishnamurty Muralidhar, Rathindra Sarathy
ESANN
2004
14 years 11 months ago
Separability of analytic postnonlinear blind source separation with bounded sources
The aim of blind source separation (BSS) is to transform a mixed random vector such that the original sources are recovered. If the sources are assumed to be statistically independ...
Fabian J. Theis, Peter Gruber