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This paper proposes a method to estimate the expected value of the Euclidean distance between two possibly incomplete feature vectors. Under the Missing at Random assumption, we show that the Euclidean distance can be modeled by a Nakagami distribution, for which the parameters we express as a function of the moments of the unknown data distribution. In our formulation the data distribution is modeled...
In this work, we propose Shrinkage k-means (Sk-means), a novel variant of k-means based on the James-Stein estimator for the mean of a multivariate normal given a single sample point. We evaluate Sk-means on both synthetic and real-world data. The proposed method outperformed standard clustering methods and also the existing method based on k-means which uses the James-Stein estimator. Results also...
When we look at our environment, we primarily pay attention to visually distinctive objects. Saliency maps are topographical maps of the visually salient parts of scenes in which such visually distinctive objects, henceforth called visually important or salient, can be easily highlighted. Computing these maps is still an open problem whose interest is growing in computer vision. Thus, in this work,...
Semi-supervised learning is a challenging topic in machine learning that has attracted much attention in recent years. The availability of huge volumes of data and the work necessary to label all these data are two of the reasons that can explain this interest. Among the various methods for semi-supervised learning, the co-training framework has become popular due to its simple formulation and promising...
The existence of missing data is a common fact in real applications which can significantly affect the data analysis process. In order to overcome this problem, many methods have been proposed in the literature. Extreme Learning Machine (ELM) has become a very popular research topic in machine learning and artificial intelligence areas due to its characteristics such as fast training procedure, good...
Ranking is an important task in information retrieval and has gained much attention in recent years. Among the most used strategies, machine learning has achieved important results. The current work proposes a new machine learning based ranking algorithm, the MLM-RANK. MLM-RANK is based on the recently proposed Minimal Learning Machine (MLM). MLM is a supervised learning method that requires the adjustment...
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