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Inspired by the fact that the final decision rule is mainly affected by a small subset of the training samples, i.e., Support Vector Machine (SVM) shows that the decision function relies on the few samples that are on or over the margin. We propose a new framework that explicitly strengthen this intuitive fact by adding an l1-norm regularizer. We give different formulations for our framework in different...
In this paper, we consider a recently proposed supervised learning problem, called online multiclass prediction with bandit setting model. Aiming at learning from partial feedback of online classification results, i.e. ??true?? when the predicting label is right or ??false?? when the predicting label is wrong, this new kind of problems arouses much of researchers' interest due to its close relations...
Aggregate outputs learning is a newly proposed setting in data mining and machine learning. It differs from the classical supervised learning setting in that, training samples are packed into bags with only the aggregate outputs (labels for classification or real values for regression) provided. This problem is associated with several kinds of application background. We focus on the aggregate outputs...
The hand gesture is the most common and natural way for human daily interaction. In this paper, we propose a novel approach to hand extraction based on active skin color model. The skin color model is first built by the non-linear transformation in YCbCr color space. Then the obtained model is applied to hand segmentation. Hand feature is extracted by calculating the seven moments of hand segmentation...
Scene classification is an important application field of multimedia information technology, whereas how to extract features from image is one of the key technologies in scene classification and recognition. A new method of extracting features is presented in this paper, it extracts features through gray level-gradient co-occurrence matrix in the neighborhood of interest points, also it can reserve...
Dynamic gesture recognition is a key issue for visual gesture-based human-computer interaction. In this paper, a dynamic gesture recognition method is proposed based on SCHMM to solve the problem, which DHMM method is high speed and low rate and CHMM method is low speed and high rate. And the gesture clustering analysis, Baum-Welch algorithm of parametric estimation and Viterbi recognition algorithm...
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