In machine learning problems, labeled data are often in short supply. One of the feasible solution for this problem is transfer learning. It can make use of the labeled data from other domain to discriminate those unlabeled data in the target domain. In this paper, we propose a transfer learning framework based on similarity matrix approximation to tackle such problems. Two practical algorithms...

optimal attributes are useful in interpretation of seismic data. two proposed methods are presented in this paper for finding optimal attributes. regularized discriminate analysis(rda) is based on 2 parameters ë, ? which called regularization parameter. the other method is principal component analysi s(pca).in this paper gas chimney detection is defined as the subject of study for ranking relev...

The Jaccard index is a standard statistics for comparing the pairwise similarity between data samples. This paper investigates the problem of estimating a Jaccard index matrix when there are missing observations in data samples. Starting from a Jaccard index matrix approximated from the incomplete data, our method calibrates the matrix to meet the requirement of positive semi-definiteness and o...

We present a novel approach to automatically extracting summary excerpts from audio and video. Our approach is to maximize the average similarity between the excerpt and the source. We first calculate a similarity matrix by comparing each pair of time samples using a quantitative similarity measure. To determine the segment with highest average similarity, we maximize the summation of the self-...

Detection of fake accounts on social networks is a challenging process. The previous methods in identification of fake accounts have not considered the strength of the users’ communications, hence reducing their efficiency. In this work, we are going to present a detection method based on the users’ similarities considering the network communications of the users. In the first step, similarity ...