908 search results - page 109 / 182 » Stochastic Finite Learning |
CORR
2006
Springer
15 years 2 months ago
2006
Springer
The Minimum Description Length principle for online sequence estimation/prediction in a proper learning setup is studied. If the underlying model class is discrete, then the total...
130
click to vote
JMLR
2002
15 years 2 months ago
2002
In this paper we prove the so-called "Meek Conjecture". In particular, we show that if a DAG H is an independence map of another DAG G, then there exists a finite sequen...
122
click to vote
CIARP
2006
Springer
15 years 4 months ago
2006
Springer
The Neural Gas (NG) is a Vector Quantization technique where a set of prototypes self organize to represent the topology structure of the data. The learning algorithm of the Neural...
108
click to vote
IJCAI
2007
15 years 4 months ago
2007
We present a general machine learning framework for modelling the phenomenon of missing information in data. We propose a masking process model to capture the stochastic nature of...
125
click to vote
UAI
2003
15 years 4 months ago
2003
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...