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IJCAI
2007
15 years 6 months ago
Simple Training of Dependency Parsers via Structured Boosting
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
Qin Iris Wang, Dekang Lin, Dale Schuurmans
NIPS
2008
15 years 6 months ago
Partially Observed Maximum Entropy Discrimination Markov Networks
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
Jun Zhu, Eric P. Xing, Bo Zhang
CORR
2011
Springer
209views Education» more  CORR 2011»
14 years 8 months ago
Close the Gaps: A Learning-while-Doing Algorithm for a Class of Single-Product Revenue Management Problems
In this work, we consider a retailer selling a single product with limited on-hand inventory over a finite selling season. Customer demand arrives according to a Poisson process,...
Zizhuo Wang, Shiming Deng, Yinyu Ye
ICASSP
2011
IEEE
14 years 8 months ago
SVM feature selection for multidimensional EEG data
In many machine learning applications, like Brain - Computer Interfaces (BCI), only high-dimensional noisy data are available rendering the discrimination task non-trivial. In thi...
Nisrine Jrad, Ronald Phlypo, Marco Congedo
170
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CORR
2012
Springer
214views Education» more  CORR 2012»
14 years 12 days ago
Sum-Product Networks: A New Deep Architecture
The key limiting factor in graphical model inference and learning is the complexity of the partition function. We thus ask the question: what are the most general conditions under...
Hoifung Poon, Pedro Domingos