vector machines
Laplacian Support Vector Machines Trained in the Primal
... In the last few years, due to the growing ubiquity of unlabeled data, much effort has been spent by the machine learning community to develop better understanding and improve the quality of classi- fiers exploiting ...
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Support Vector Machines for Design Space Exploration
... space and can become numerically demanding for high input dimensions. The alternative proposed in this paper is the use of support vector machines (SVM), which can robustly clas- sify even very complex sets ...
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Bird Species Recognition Using Support Vector Machines
... Support vector machines and other kernel-based methods have become a popular tool in many kinds of machine learn- ing ...support vector machines, refer to ...
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Consensus-Based Distributed Support Vector Machines
... 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 complexity, ...
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Support Vector Machines for Anatomical Joint Constraint Modelling
... Abstract— The accurate simulation of anatomical joint models is becoming increasingly important for both realistic animation and diagnostic medical applications. Recent models have exploited unit quaternions to eliminate ...
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Support Vector Machines for Paraphrase Identification and Corpus Construction
... The lack of readily-available large cor- pora of aligned monolingual sentence pairs is a major obstacle to the devel- opment of Statistical Machine Transla- tion-based paraphrase models. In this paper, we describe the ...
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Extracting Word Sequence Correspondences with Support Vector Machines
... This paper proposes a learning and extract- ing method of bilingual word sequence correspon- dences from non-aligned parallel corpora with Sup- port Vector Machines (SVMs) (Vapnik, 1999). SVMs are ones of ...
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Extracting Important Sentences with Support Vector Machines
... Extracting sentences that contain important in- formation from a document is a form of text summarization. The technique is the key to the automatic generation of summaries similar to those written by humans. To achieve ...
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Robustness and Regularization of Support Vector Machines
... Support Vector Machines (SVMs for short) originated in Boser et al. (1992) and can be traced back to as early as Vapnik and Lerner (1963) and Vapnik and Chervonenkis (1974). They continue to be one of the ...
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Probabilistic Sentence Reduction Using Support Vector Machines
... support vector machine (SVM) is a binary classification method, while the sentence reduction problem is formulated as multiple classification, we have to find a method to adapt support vector ...
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Quadratic Surface Support Vector Machines with Applications.
... Support vector machines (SVM) are effective and commonly used classification ...support vector machine (QSSVM) models for binary classification directly using a quadratic function instead of using a ...
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Shallow Semantic Parsing using Support Vector Machines
... For the initial experiments, we adopted the approach described by Gildea and Jurafsky (2002) (G&J) and eval- uated a series of modifications to improve its perfor- mance. In the experiments reported here, we first ...
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Virtual Examples for Text Classification with Support Vector Machines
... We explore how virtual examples (artifi- cially created examples) improve perfor- mance of text classification with Support Vector Machines (SVMs). We propose techniques to create virtual examples for text ...
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Areas categorization by operating Support Vector Machines
... In recent years, Support Vector Machines (SVMs) have demonstrated excellent functioning in a variety of area categorization problems. This paper explains areas categorization by operating SVMs. The SVM is ...
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Spatio-temporal avalanche forecasting with Support Vector Machines
... The output of the binary classification system can be characterized by several basic measures computed from the contingency table. Concerning natural hazards, different possible forms and interpretations of the forecast ...
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Support vector machines for texture classification
... Abstract—This paper investigates the application of support vector machines (SVMs) in texture classification. Instead of relying on an external feature extractor, the SVM receives the gray-level values of ...
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Support vector machines in projects risk classification
... Projects are fundamental to organizations, but they are subject to the occurrence of risks, which can affect their success. Therefore, project managers seek to manage risks by demanding decisions about their treatment. A ...
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Chunking with Support Vector Machines
... In this paper, we introduce a uniform framework for chunking task based on Support Vector Machines (SVMs). Experimental results on WSJ corpus show that our method outperforms other conventional ma- chine ...
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Sparseness of Support Vector Machines
... Support vector machines (SVMs) construct decision functions that are linear combinations of kernel evaluations on the training set. The samples with non-vanishing coefficients are called support vectors. In ...
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An Information Criterion for Variable Selection in Support Vector Machines
... For support vector machines only very few information criteria have been developed. The kernel regularisation information criterion (KRIC) of Kobayashi and Komaki (2006) was originally pro- posed for ...
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