116 search results - page 10 / 24 » Monte Carlo Hierarchical Model Learning |
NIPS
2001
13 years 10 months ago
2001
This paper proposes an approach to classification of adjacent segments of a time series as being either of classes. We use a hierarchical model that consists of a feature extract...
WSC
1998
13 years 10 months ago
1998
In simulation modeling and analysis, there are two situations where there is uncertainty about the number of parameters needed to specify a model. The first is in input modeling w...
AAAI
2012
11 years 11 months ago
2012
This paper concerns learning and prediction with probabilistic models where the domain sizes of latent variables have no a priori upper-bound. Current approaches represent prior d...
NIPS
2003
13 years 10 months ago
2003
In models that define probabilities via energies, maximum likelihood learning typically involves using Markov Chain Monte Carlo to sample from the model’s distribution. If the ...
WSC
2004
13 years 10 months ago
2004
HDPS is a practical system for designing modeling paradigms, creating hierarchal model definitions, and evaluating multi-paradigm models - particularly in business and finance. HD...