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The word-level sentiment analysis is an essential issue in opinion mining. One challenge in this field is that not so many lexical items as expected have been labeled with sentimental opinions, especially in Chinese. There are two ways of rating words: one is manual marking which costs lots of resources, energy and time; the other is machine marking which is efficient, convenient and time-saving....
In the procedure of China's market-oriented reforms of interest rates, the interest-rate risk becomes increasingly apparent. Analyzing the existing studies and the interbank offered rate trend, this paper finds that LS-SVM, which is short for Least Squares Support Vector Machines, is excel in nonlinear data approximation, which is suitable for interest rate forecasting. Firstly, the paper established...
Deep Convolutional Neural Networks (DCNN) have established a remarkable performance benchmark in the field of image classification, displacing classical approaches based on hand-tailored aggregations of local descriptors. Yet DCNNs impose high computational burdens both at training and at testing time, and training them requires collecting and annotating large amounts of training data. Supervised...
Taking motivation from Twin Support Vector Machine (TWSVM), Peng (2009) attempted to propose Twin Support Vector Regression (TSVR) where regressor was obtained via solving pair of Quadratic Programming Problems(QPPs). However the discussed formulation was not on the lines of TWSVM and had some restrictions. In this paper we propose formulation termed as Twin Support Vector Machine based Regression(TWSVR)...
The optimization method based extreme learning machine (optimization-based ELM) is generalized from single-hidden-layer feed-forward neural networks (SLFNs) by making use of kernels instead of neuron-alike hidden nodes. This approach is known for its high scalability, low computational complexity, and mild optimization constrains. The multi-kernel learning (MKL) framework Simple MKL iteratively determines...
A non-parametric approach for distinguishing between individuals by means of recorded eye movements is suggested. The method is based on the principles of stochastic anomaly detection and relies on measured data for probability distribution estimation and evaluation. For visual stimuli that excite the essential nonlinear dynamics of the human oculomotor system, mean gaze trajectories and characterizations...
This paper describes a technical problem of obtaining a unique SDL entity identifier using SDL/SystemC co-modeling. The problem occurs during scientific research in co-modeling field as well as work under real projects. Solution consists in redefinition the standard function of SDL simulation kernel for getting access to entity name and then conversion its name to a unique identifier. The paper explains...
In conventional support vector data description (SVDD), for each class we look for the smallest sphere that encloses its data. in the decision phase a sample is classified into class i only when the value of the ith decision function is positive. following this architecture, an unclassifiable region (s) can be appeared if the values of more than one decision function are positives. To overcome this...
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