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TREC
2004
15 years 7 months ago
The University of Michigan in Novelty 2004
This year we participated in the Novelty track. To find the relevant sentences, we combine sentence salience features that are inherited from text summarization domain with other ...
Günes Erkan
COLING
2008
15 years 8 months ago
Extractive Summarization Using Supervised and Semi-Supervised Learning
It is difficult to identify sentence importance from a single point of view. In this paper, we propose a learning-based approach to combine various sentence features. They are cat...
Kam-Fai Wong, Mingli Wu, Wenjie Li
ICML
2004
IEEE
15 years 12 months ago
Gradient LASSO for feature selection
LASSO (Least Absolute Shrinkage and Selection Operator) is a useful tool to achieve the shrinkage and variable selection simultaneously. Since LASSO uses the L1 penalty, the optim...
Yongdai Kim, Jinseog Kim
ALT
2010
Springer
15 years 8 months ago
Consistency of Feature Markov Processes
We are studying long term sequence prediction (forecasting). We approach this by investigating criteria for choosing a compact useful state representation. The state is supposed t...
Peter Sunehag, Marcus Hutter
EMNLP
2009
15 years 4 months ago
Simple Coreference Resolution with Rich Syntactic and Semantic Features
Coreference systems are driven by syntactic, semantic, and discourse constraints. We present a simple approach which completely modularizes these three aspects. In contrast to muc...
Aria Haghighi, Dan Klein