Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...
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Abstract: Graph matching is a widely studied and applied field, with Graph Edit Distance (GED) serving as a fundamental metric for evaluating the similarity between graphs. As an NP-hard problem in ...
A 34-year-old with a $2.9 million portfolio has ambitious goals and shared them with the Chubby FIRE Reddit community. The couple is on track to achieve their goals if they keep their spending under ...
ABSTRACT: To effectively evaluate a system that performs operations on UML class diagrams, it is essential to cover a large variety of different types of diagrams. The coverage of the diagram space ...
In the age when data is everything to a business, managers and analysts alike are looking to emerging forms of databases to paint a clear picture of how data is delivering to their businesses. The ...
The increasing reliance on knowledge graphs parallels that of Artificial Intelligence for three irrefutable reasons. They’re the most effective means of preparing data for statistical AI, creditable ...
Abstract: In various areas of computer science and mathematics, including scientific computing, task scheduling and VLSI design, the graph concept is used for modeling purposes, and graph partitioning ...
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