Abstract. We present three streaming algorithms that ( , δ)− approximate 1 the number of triangles in graphs. Similar to the previous algorithms [3], the space usage of presente...
Abstract. When direct measurement of model parameters is not possible, these need to be inferred indirectly from calibration data. To solve this inverse problem, an algorithm that ...
Scatterograms of the images of training set vectors in the hidden space help to evaluate the quality of neural network mappings and understand internal representations created by t...
An empirical study is performed on the local-optimum space of graph bipartitioning. We examine some statistical features of the fitness landscape. They include the cost-distance c...
We formulate the problem of graph inference where part of the graph is known as a supervised learning problem, and propose an algorithm to solve it. The method involves the learni...