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EMNLP
2006
13 years 9 months ago
Competitive generative models with structure learning for NLP classification tasks
In this paper we show that generative models are competitive with and sometimes superior to discriminative models, when both kinds of models are allowed to learn structures that a...
Kristina Toutanova
ACL
2003
13 years 8 months ago
Parametric Models of Linguistic Count Data
It is well known that occurrence counts of words in documents are often modeled poorly by standard distributions like the binomial or Poisson. Observed counts vary more than simpl...
Martin Jansche
IADIS
2003
13 years 8 months ago
Hypertext Classification: A Multiagent Model for Adaptive Learning Algorithm
The problem of hypertext classification deals with objects possessing more complex information structure than the plain text has. Present hypertext classification systems show the...
Stanislav Baglei
UAI
1996
13 years 8 months ago
Asymptotic Model Selection for Directed Networks with Hidden Variables
We extend the Bayesian Information Criterion (BIC), an asymptotic approximation for the marginal likelihood, to Bayesian networks with hidden variables. This approximation can be ...
Dan Geiger, David Heckerman, Christopher Meek
ICML
2010
IEEE
13 years 8 months ago
Asymptotic Analysis of Generative Semi-Supervised Learning
Semi-supervised learning has emerged as a popular framework for improving modeling accuracy while controlling labeling cost. Based on an extension of stochastic composite likeliho...
Joshua Dillon, Krishnakumar Balasubramanian, Guy L...