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TSMC
2010
13 years 6 months ago
Probability Density Estimation With Tunable Kernels Using Orthogonal Forward Regression
A generalized or tunable-kernel model is proposed for probability density function estimation based on an orthogonal forward regression procedure. Each stage of the density estimat...
Sheng Chen, Xia Hong, Chris J. Harris
TIP
2010
141views more  TIP 2010»
13 years 6 months ago
Efficient Particle Filtering via Sparse Kernel Density Estimation
Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
Amit Banerjee, Philippe Burlina
JMLR
2011
133views more  JMLR 2011»
13 years 6 months ago
Operator Norm Convergence of Spectral Clustering on Level Sets
Following Hartigan (1975), a cluster is defined as a connected component of the t-level set of the underlying density, that is, the set of points for which the density is greater...
Bruno Pelletier, Pierre Pudlo
TIT
2008
85views more  TIT 2008»
13 years 11 months ago
Undersmoothed Kernel Entropy Estimators
We develop a "plug-in" kernel estimator for the differential entropy that is consistent even if the kernel width tends to zero as quickly as 1/N, where N is the number of...
Liam Paninski, Masanao Yajima
GRAPHICSINTERFACE
2008
14 years 27 days ago
Single-pass GPU solid voxelization for real-time applications
In this paper, we present a single-pass technique to voxelize the interior of watertight 3D models with high resolution grids in realtime during a single rendering pass. Further, ...
Elmar Eisemann, Xavier Décoret