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EMNLP
2008
13 years 9 months ago
Learning with Compositional Semantics as Structural Inference for Subsentential Sentiment Analysis
Determining the polarity of a sentimentbearing expression requires more than a simple bag-of-words approach. In particular, words or constituents within the expression can interac...
Yejin Choi, Claire Cardie
FLAIRS
2006
13 years 9 months ago
Decomposing Local Probability Distributions in Bayesian Networks for Improved Inference and Parameter Learning
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
Adam Zagorecki, Mark Voortman, Marek J. Druzdzel
BMCBI
2010
229views more  BMCBI 2010»
13 years 7 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck
AAAI
2007
13 years 10 months ago
Learning and Inference for Hierarchically Split PCFGs
Treebank parsing can be seen as the search for an optimally refined grammar consistent with a coarse training treebank. We describe a method in which a minimal grammar is hierarc...
Slav Petrov, Dan Klein
PADL
2012
Springer
12 years 3 months ago
LearnPADS + + : Incremental Inference of Ad Hoc Data Formats
An ad hoc data source is any semi-structured, non-standard data source. The format of such data sources is often evolving and frequently lacking documentation. Consequently, off-t...
Kenny Qili Zhu, Kathleen Fisher, David Walker