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» Learning Rules from Distributed Data
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ICIP
2003
IEEE
16 years 4 months ago
Adaptive rule-based recognition of events in video sequences
Knowledge-based fuzzy inference and neural learning are used in this paper in order to model the event recognition task in semantic video analysis. The advantage of their use is t...
Vassilis Tzouvaras, Gabriel Tsechpenakis, Giorgos ...
AMAI
2004
Springer
15 years 8 months ago
Using the Central Limit Theorem for Belief Network Learning
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Ian Davidson, Minoo Aminian
ICML
2009
IEEE
16 years 3 months ago
A stochastic memoizer for sequence data
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
Frank Wood, Cédric Archambeau, Jan Gasthaus...
IDA
2002
Springer
15 years 2 months ago
Online classification of nonstationary data streams
Most classification methods are based on the assumption that the data conforms to a stationary distribution. However, the real-world data is usually collected over certain periods...
Mark Last
RECOMB
2000
Springer
15 years 6 months ago
Using Bayesian networks to analyze expression data
DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a "snapshot" of transcription levels within the c...
Nir Friedman, Michal Linial, Iftach Nachman, Dana ...