نتایج جستجو برای: maximum entropy me

تعداد نتایج: 399628  

2006
Lluis Marquez

Recent literature on text-tagging reported successful results by applying Maximum Entropy (ME) models. In general, ME taggers rely on carefully selected binary features, which try to capture discriminant information from the training data. This paper introduces a standard setting of binary features, inspired by the literature on named-entity recognition and text chunking, and derives correspond...

2007
Chih-Yuan Tseng HC Lee

We propose a maximum entropy (ME) based approach to smooth noise not only in data but also to noise amplified by second order derivative calculation of the data especially for electroencephalography (EEG) studies. The approach includes two steps, applying method of ME to generate a family of filters and minimizing noise variance after applying these filters on data selects the preferred one wit...

2006
Vanessa Sandrini Marcello Federico Mauro Cettolo

Recent literature on text-tagging reported successful results by applying Maximum Entropy (ME) models. In general, ME taggers rely on carefully selected binary features, which try to capture discriminant information from the training data. This paper introduces a standard setting of binary features, inspired by the literature on named-entity recognition and text chunking, and derives correspond...

Journal: :IEEE Trans. Speech and Audio Processing 2000
Stanley F. Chen Ronald Rosenfeld

In certain contexts, maximum entropy (ME) modeling can be viewed as maximum likelihood (ML) training for exponential models, and like other ML methods is prone to overfitting of training data. Several smoothing methods for ME models have been proposed to address this problem, but previous results do not make it clear how these smoothing methods compare with smoothing methods for other types of ...

Journal: :Acta Crystallographica Section A Foundations of Crystallography 2002

Journal: :Journal of physics 2022

In order to realize the reliability evaluation of small sample size aviation support system with known prior information, Bayes methods are given by using second-order moment equivalent method, relative least squares method (RLS method), maximum entropy (ME method) and Chebyshev polynomial respectively, accuracies above synthesis compared analysed through an example. The results show that ME RL...

2006
Matt Gedigian John Bryant Srinivas Narayanan Branimir Ciric

Metaphors are ubiquitous in language and developing methods to identify and deal with metaphors is an open problem in Natural Language Processing (NLP). In this paper we describe results from using a maximum entropy (ME) classifier to identify metaphors. Using the Wall Street Journal (WSJ) corpus, we annotated all the verbal targets associated with a set of frames which includes frames of spati...

2006
Minyoung Kim Yushi Jing Vladimir Pavlovic James M. Rehg

The problem of labeling (or segmenting) sequences is very important in many applications such as part-of-speech tagging in natural language processing, multimodal object detection in computer vision, and DNA/protein structure prediction in bioinformatics. Conditional Random Fields (CRFs) of [1] are known to be the best sequence models ever for the problem. CRF is a conditional model, P (s|y), i...

2006
Jui-Feng Yeh Chung-Hsien Wu Wei-Yen Wu

This study describes an approach to edit disfluency detection based on maximum entropy (ME) using contextual features for rich transcription of spontaneous speech. The contextual features contain word-level, chunk-level and sentence-level features for edit disfluency modeling. Due to the problem of data sparsity, word-level features are determined according to the taxonomy of the primary featur...

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