[PDF] Top 20 Extracting Important Sentences with Support Vector Machines
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Extracting Important Sentences with Support Vector Machines
... ument, important sentences were manually ex- tracted at summarization rates of 10%, 30%, and ...of sentences in a doc- ument not the number of ... See full document
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Infinite ensemble learning with support vector machines
... In this section, we introduce two important properties of the SVM-based framework. First we show that the framework allows us to embed multiple base learning models together with a simple summation over the ... See full document
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Robustness and Regularization of Support Vector Machines
... The connection of robustness and regularization in the SVM context is important for the follow- ing reasons. First, it gives an alternative and potentially powerful explanation of the generalization ability of the ... See full document
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Quadratic Surface Support Vector Machines with Applications.
... an important task in information extraction from data. Support vector machines (SVM) are effective and commonly used classification ...surface support vector machine (QSSVM) ... See full document
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Support vector machines with adaptive Lq penalty
... to shrink small |w|’s to exact zeros and hence selects important variables. As pointed out by Theorem 2 in Knight and Fu (2000), when q > 1 the amount of shrinkage towards zero increases with the magnitude of ... See full document
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Consensus-Based Distributed Support Vector Machines
... train support vector machines when training data are distributed across different nodes, and their communication to a centralized processing unit is prohibited due to, for example, communication ... See full document
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Support Vector Machines for Design Space Exploration
... For all DoE strategies, especially the ones based on active learning, it is important to know the design space. Only if the design space is known the measurement points can be placed inside it in an optimal way. ... See full document
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Extracting Definitions and Hypernym Relations relying on Syntactic Dependencies and Support Vector Machines
... definitional sentences, i.e., sentences that contain at least one hypernym ...is important by itself for many tasks like Question Answering (Cui et ... See full document
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Filtered selection coupled with support vector machines generate a functionally relevant prediction model for colorectal cancer
... On the other hand, the hybrid mRMR + REPT was the best performing model using the tenfold cross validation. This is because REPT is a fast decision tree learning by downsizing of decision trees. It removes sections of ... See full document
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Learning to Classify Ordinal Data: The Data Replication Method
... Classification of ordinal data is one of the most important tasks of relation learning. This paper introduces a new machine learning paradigm specifically intended for classification problems where the classes ... See full document
37
Support Vector Machines for Anatomical Joint Constraint Modelling
... increasingly important for both realistic animation and diagnostic medical ...using Support Vector Machines (SVMs) is proposed which attempts to address the limitations of current constraint ... See full document
5
Support vector machines for texture classification
... The simplest way to characterize the variability in a texture pattern is by noting the gray-level values of the raw pixels. This set of gray values becomes the feature set on which the classification is based. An ... See full document
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Support vector machines in projects risk classification
... A project is a temporary effort undertaken to create a product, service or exclusive result, are essential enterprises for the implementation of organizational strategies and fundamental for the growth of companies (PMI, ... See full document
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Extracting Word Sequence Correspondences with Support Vector Machines
... As both training and test corpora, 1,000 sentences were used. The translation pairs which are already marked up in the corpora were corrected to the form described in section 3.4 to be used as the positive ... See full document
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Clustering Via Supervised Support Vector Machines
... In [4] it is shown that the for this class of hyperplanes the VC dimension can be bounded in terms of another quantity, the margin. The margin is defined as the minimal distance of a sample to the decision surface (see ... See full document
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Online Full Text
... Fuzzy Support Vector Machines (PSOFuzzySVM) to predict oil well gas lift performance and production optimization in a ...Fuzzy Support Vector Machines (FuzzySVM), which is a ... See full document
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Laplacian Support Vector Machines Trained in the Primal
... Transductive Support Vector Machines (Vapnik, 2000) and its different implementations, such as TSVM (Joachims, 1999) or S 3 VM (Demiriz and Bennett, 2000; Chapelle et ...Laplacian Support ... See full document
36
A Hierarchy of Support Vector Machines for Pattern Detection
... We presented a general method for exploring a space of hypotheses based on a coarse-to-fine hier- archy of SVM classifiers and applied it to the special case of detecting faces in cluttered images. As opposed to a single ... See full document
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Sparse Deconvolution Using Support Vector Machines
... applications. Support vector machine (SVM) algorithms show a series of characteristics, such as sparse solutions and implicit regularization, which make them attractive for solving sparse deconvolution ... See full document
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Online Full Text
... for support vector machines in a hybrid Data Mining and Case-Based Reasoning system which incorporates a vector model to help transfer textual information to numerical vector in order ... See full document
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