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136
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CGF
2005
252views more  CGF 2005»
15 years 3 months ago
Support Vector Machines for 3D Shape Processing
We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which...
Florian Steinke, Bernhard Schölkopf, Volker B...
116
Voted
TSP
2008
119views more  TSP 2008»
15 years 3 months ago
Universal Weighted MSE Improvement of the Least-Squares Estimator
Since the seminal work of Stein in the 1950s, there has been continuing research devoted to improving the total meansquared error (MSE) of the least-squares (LS) estimator in the l...
Yonina C. Eldar
123
Voted
AI
2000
Springer
15 years 3 months ago
Stochastic dynamic programming with factored representations
Markov decisionprocesses(MDPs) haveproven to be popular models for decision-theoretic planning, but standard dynamic programming algorithms for solving MDPs rely on explicit, stat...
Craig Boutilier, Richard Dearden, Moisés Go...
112
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COMPSEC
2002
185views more  COMPSEC 2002»
15 years 3 months ago
A framework for understanding and predicting insider attacks
In this paper an insider attack is considered to be deliberate misuse by those who are authorized to use computers and networks. Applying this definition in real-life settings to ...
E. Eugene Schultz
SIAMCO
2000
71views more  SIAMCO 2000»
15 years 3 months ago
On a Perturbation Approach for the Analysis of Stochastic Tracking Algorithms
In this paper, a perturbation expansion technique is introduced to decompose the tracking error of a general adaptive tracking algorithm in a linear regression model. This method ...
Rafik Aguech, Eric Moulines, Pierre Priouret