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» Better Informed Training of Latent Syntactic Features
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ICPR
2006
IEEE
14 years 8 months ago
Feature selection based on the training set manipulation
A novel filter feature selection technique is introduced. The method exploits the information conveyed by the evolution of the training samples weights similarly to the Adaboost a...
Pavel Krízek, Josef Kittler, Václav ...
IDA
2007
Springer
14 years 1 months ago
Combining Bagging and Random Subspaces to Create Better Ensembles
Random forests are one of the best performing methods for constructing ensembles. They derive their strength from two aspects: using random subsamples of the training data (as in b...
Pance Panov, Saso Dzeroski
EMNLP
2009
13 years 5 months ago
On the Role of Lexical Features in Sequence Labeling
We use the technique of SVM anchoring to demonstrate that lexical features extracted from a training corpus are not necessary to obtain state of the art results on tasks such as N...
Yoav Goldberg, Michael Elhadad
ACL
2012
11 years 10 months ago
Modeling Sentences in the Latent Space
Sentence Similarity is the process of computing a similarity score between two sentences. Previous sentence similarity work finds that latent semantics approaches to the problem ...
Weiwei Guo, Mona T. Diab
ACL
2011
12 years 11 months ago
A Large Scale Distributed Syntactic, Semantic and Lexical Language Model for Machine Translation
This paper presents an attempt at building a large scale distributed composite language model that simultaneously accounts for local word lexical information, mid-range sentence s...
Ming Tan, Wenli Zhou, Lei Zheng, Shaojun Wang