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119
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TIP
2010
141views more  TIP 2010»
14 years 7 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
87
Voted
ECCV
2002
Springer
16 years 2 months ago
Nonlinear Shape Statistics in Mumford-Shah Based Segmentation
We present a variational integration of nonlinear shape statistics into a Mumford?Shah based segmentation process. The nonlinear statistics are derived from a set of training silho...
Christoph Schnörr, Daniel Cremers, Timo Kohlb...
ISSRE
2000
IEEE
15 years 5 months ago
Module Size Distribution and Defect Density
Data from several projects show a significant relationship between the size of a module and its defect density. Here we address implications of this observation. Does the overall ...
Yashwant K. Malaiya, Jason Denton
COLT
2010
Springer
14 years 10 months ago
Forest Density Estimation
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
Anupam Gupta, John D. Lafferty, Han Liu, Larry A. ...
100
Voted
MLDM
2007
Springer
15 years 6 months ago
Outlier Detection with Kernel Density Functions
Abstract. Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel unsupervised algorithm for outlier detec...
Longin Jan Latecki, Aleksandar Lazarevic, Dragolju...