12 search results - page 2 / 3 » Incremental Sigmoid Belief Networks for Grammar Learning |
EMNLP
2007
13 years 6 months ago
2007
We use a generative history-based model to predict the most likely derivation of a dependency parse. Our probabilistic model is based on Incremental Sigmoid Belief Networks, a rec...
JMLR
2012
11 years 7 months ago
2012
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
IJON
2007
13 years 4 months ago
2007
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
AAAI
2010
13 years 6 months ago
2010
Many problems require repeated inference on probabilistic graphical models, with different values for evidence variables or other changes. Examples of such problems include utilit...
CHI
2011
ACM
12 years 8 months ago
2011
ACM
Extracting useful knowledge from large network datasets has become a fundamental challenge in many domains, from scientific literature to social networks and the web. We introduc...