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UAI
2000
13 years 8 months ago
Being Bayesian about Network Structure
In many domains, we are interested in analyzing the structure of the underlying distribution, e.g., whether one variable is a direct parent of the other. Bayesian model selection a...
Nir Friedman, Daphne Koller
NIPS
2004
13 years 8 months ago
Bayesian inference in spiking neurons
We propose a new interpretation of spiking neurons as Bayesian integrators accumulating evidence over time about events in the external world or the body, and communicating to oth...
Sophie Deneve
IJCNN
2007
IEEE
14 years 1 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
BMCBI
2006
169views more  BMCBI 2006»
13 years 7 months ago
Machine learning techniques in disease forecasting: a case study on rice blast prediction
Background: Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their ...
Rakesh Kaundal, Amar S. Kapoor, Gajendra P. S. Rag...
UIST
1993
ACM
13 years 11 months ago
VB2: An Architecture for Interaction in Synthetic Worlds
This paper describes the VB2 architecture for the construction of three-dimensional interactive applications. The system's state and behavior are uniformly represented as a n...
Enrico Gobbetti, Jean-Francis Balaguer, Daniel Tha...