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TSMC
2010
13 years 5 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
IJCNN
2007
IEEE
14 years 5 months ago
Probability Density Function Estimation Using Orthogonal Forward Regression
— Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression tec...
Sheng Chen, Xia Hong, Chris J. Harris
ASPDAC
1999
ACM
100views Hardware» more  ASPDAC 1999»
14 years 3 months ago
Node Sampling Technique to Speed Up Probability-Based Power Estimation Methods
We propose a new technique called node sampling to speed up the probability-based power estimation methods. It samples and processes only a small portion of total nodes to estimat...
Hoon Choi, Hansoo Kim, In-Cheol Park, Seung Ho Hwa...
TIME
1994
IEEE
14 years 3 months ago
Belief Revision in a Discrete Temporal Probability-Logic
We describe a discrete time probabilitylogic for use as the representation language of a temporal knowledge base. In addition to the usual expressive power of a discrete temporal ...
Scott D. Goodwin, Howard J. Hamilton, Eric Neufeld...
COMPLEXITY
2006
144views more  COMPLEXITY 2006»
13 years 11 months ago
BML revisited: Statistical physics, computer simulation, and probability
Statistical physics, computer simulation and discrete mathematics are intimately related through the study of shared lattice models. These models lie at the foundation of all thre...
Raissa M. D'Souza