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This paper presents a supervised data imputation based on the class-dependent matrix factors, which are generated during matrix factorization. The proposed ridge alternating least squares imputation uses class information to create substituted values, which approximate the characteristics of their corresponding classes, for missing entries. In the training phase, the incomplete data with label information...
Traditional NIE (Newspaper in Education), which is the study of how to utilize any educational resources in the newspaper in the classroom, has been studied for a long time. However, it has a one-way interaction characteristic and available media are limited. In addition, it has difficulty capturing the latest "hot" issues or recognizing any public opinions. In this paper, we propose a platform...
Estimation of depth in a Neural Network (NN) or Artificial Neural Network (ANN) is an integral as well as complicated process. In this article, we propose a way of using the transformation of functions combined with recursive nature to have an adaptive, transcursive algorithm to represent the backpropagation concept used in deep learning for a Multilayer Perceptron Network. Each function can be used...
In this paper, we propose a location-based large-scale landmark image recognition scheme for mobile devices such as smart phones. To achieve this goal, we collected landmark images all around the world, which were available on the web. For each landmark, we detected interest points and constructed their feature descriptors using SURF. Next, we performed a statistical analysis on the local features...
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