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» COPICA - independent component analysis via copula technique...
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ORL
2011
14 years 5 months ago
Convex approximations to sparse PCA via Lagrangian duality
We derive a convex relaxation for cardinality constrained Principal Component Analysis (PCA) by using a simple representation of the L1 unit ball and standard Lagrangian duality. ...
Ronny Luss, Marc Teboulle
CCS
2008
ACM
15 years 18 days ago
Ether: malware analysis via hardware virtualization extensions
Malware has become the centerpiece of most security threats on the Internet. Malware analysis is an essential technology that extracts the runtime behavior of malware, and supplie...
Artem Dinaburg, Paul Royal, Monirul I. Sharif, Wen...
ASPLOS
1996
ACM
15 years 2 months ago
Analysis of Branch Prediction Via Data Compression
Branch prediction is an important mechanism in modern microprocessor design. The focus of research in this area has been on designing new branch prediction schemes. In contrast, v...
I-Cheng K. Chen, John T. Coffey, Trevor N. Mudge
QEST
2005
IEEE
15 years 4 months ago
Fluid Flow Approximation of PEPA models
In this paper we present a novel performance analysis technique for large-scale systems modelled in the stochastic process algebra PEPA. In contrast to the well-known approach of ...
Jane Hillston
CORR
2010
Springer
189views Education» more  CORR 2010»
14 years 9 months ago
Robust PCA via Outlier Pursuit
Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it ...
Huan Xu, Constantine Caramanis, Sujay Sanghavi