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IJAR
2008
119views more  IJAR 2008»
14 years 8 months ago
Least committed basic belief density induced by a multivariate Gaussian: Formulation with applications
We consider here the case where our knowledge is partial and based on a betting density function which is n-dimensional Gaussian. The explicit formulation of the least committed b...
Francois Caron, Branko Ristic, Emmanuel Duflos, Ph...
ICCAD
2008
IEEE
97views Hardware» more  ICCAD 2008»
15 years 6 months ago
Guiding global placement with wire density
—This paper presents an efficient technique for the estimation of the routed wirelength during global placement using the wire density of the net. The proposed method identifie...
Kalliopi Tsota, Cheng-Kok Koh, Venkataramanan Bala...
PKDD
2005
Springer
130views Data Mining» more  PKDD 2005»
15 years 3 months ago
Unsupervised Discretization Using Tree-Based Density Estimation
This paper presents an unsupervised discretization method that performs density estimation for univariate data. The subintervals that the discretization produces can be used as the...
Gabi Schmidberger, Eibe Frank
SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
14 years 11 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
87
Voted
KDD
2004
ACM
154views Data Mining» more  KDD 2004»
15 years 10 months ago
Diagnosing extrapolation: tree-based density estimation
There has historically been very little concern with extrapolation in Machine Learning, yet extrapolation can be critical to diagnose. Predictor functions are almost always learne...
Giles Hooker