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...
— 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...
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...
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...
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...