Support Vector Machines
On qualitative robustness of support vector machines
... Since support vector machines play an important role in statistical machine learning, investigating their performance in the presence of moderate model violations is a crucial topic — the more so as ...
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Bankruptcy prediction with support vector machines
... of support vector machines (SVMs) for prediction of German companies’ failure that is based on 24 financial ratios being grouped into four categories, namely profitability, leverage, liquidity and ...
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Robustness and Regularization of Support Vector Machines
... We consider regularized support vector machines (SVMs) and show that they are precisely equiva- lent to a new robust optimization formulation. We show that this equivalence of robust optimization and ...
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Support Vector Machines for Design Space Exploration
... For linear problems factor analysis or principal component analysis (PCA) are well established methods for handling high dimensional data and performing dimensionality reduc- tion, e.g. as preprocessing tools for solving ...
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Support Vector Machines for Face Recognition
... etc. Support vector machine (SVM) learning is a recent technology that gives a decent broad view performance this paper given the most recent algorithms developed for face recognition and tries to give an ...
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Convolutional Support Vector Machines For Image Classification
... The idea of combining support vector machines and convolutional neural networks into a hybrid classifier has been investigated in previous work. In (Huang and LeCun, 2006) a CNN was trained was on ...
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Choosing Multiple Parameters for Support Vector Machines
... Abstract. The problem of automatically tuning multiple parameters for pattern recognition Support Vector Machines (SVMs) is considered. This is done by minimizing some estimates of the generalization ...
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Support vector machines for texture classification
... these, support vector machines (SVMs) would appear to be a good candidate because of their ability to generalize in high-dimensional spaces, such as spaces spanned by texture ...
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Predicting Bankruptcy with Support Vector Machines
... the support vector machine (SVM) – to corporate bankruptcy ...that support vector machines are capable of extracting useful infor- mation from financial data, although extensive data ...
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Rating Companies with Support Vector Machines
... the support vector machine (SVM) – to the field of corporate bankruptcy ...that support vector machines are capable of extracting useful information from financial data although ...
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Binarized support vector machines
... The support vector machines (SVM) (Cortes and Vapnik 1995) approach is based on margin maximiza- tion, which consists in finding the separating hyper- plane that is farthest from the closest ...
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A Tutorial on Support Vector Machines for Pattern Recognition
... linear Support Vector Machines (SVMs) for separable and non-separable data, working through a non-trivial example in ...how support vector training can be practically implemented, and ...
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Scalable Multilevel Support Vector Machines
... for support vector machines on large- scale training data is often an expensive computational ...the support vectors are obtained and gradually refined at multiple levels of coarseness of the ...
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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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Numerical Experiments with Support Vector Machines
... the Support Vector Machines for the environmental and pollution spatial data classification has been considered in our previous papers (Kanevski et al 1999, Gilardi and Kanevski ...
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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 ...
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Support Vector Machines and Multi-Task Learning
... side, Support Vector Machines (SVMs) are popular models in machine learning due to its multiple characteristics and the theory that supports ...
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Support Vector Machines
... By examining the dual form of the optimization problem, we gained sig- nificant insight into the structure of the problem, and were also able to write the entire algorithm in terms of only inner products between input ...
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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 ...
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Support vector machines in projects risk classification
... using Support Vector Machines with advantages over traditional methods, since effects such as reverse classification and ambiguity in the risk hierarchy are ...
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