Researchers develop software package to solve a problem called the “S-unit equation,” with the hope to solve centuries-old mathematical problems Computer Science |
- Researchers develop software package to solve a problem called the “S-unit equation,” with the hope to solve centuries-old mathematical problems
- Request Review for Computational Solution of the NP-completeness
- A New Model of Artificial Intelligence: Application to Data II
| Posted: 14 Apr 2019 09:14 AM PDT |
| Request Review for Computational Solution of the NP-completeness Posted: 14 Apr 2019 07:46 PM PDT The P versus NP problem is a major unsolved problem in computer science. This is considered by many to be the most important open problem in the field. If any single NP-complete problem can be solved in polynomial time, then every NP problem has a polynomial time algorithm. We prove the known NP-complete problem BETWEENNESS can be solved in polynomial time. We also provide a Computer Code and Software which decides the instances of this problem in polynomial time. The proof and code is in GitHub Inc: https://github.com/frankvegadelgado/P-NP Thanks in advance!!! [link] [comments]  |
| A New Model of Artificial Intelligence: Application to Data II Posted: 10 Apr 2019 02:23 PM PDT In this article, I'm going to apply the new, polynomial time model of artificial intelligence that I've developed to the MNIST numerical character dataset, as well as two small image datasets made with an ordinary iPhone camera. The MNIST dataset was analyzed on a supervised basis, with a success rate of 95.402%, where success is measured by the percentage of predictions that are consistent with the classification data. The other two datasets were analyzed on an unsupervised basis, with an average success rate of 95.834%. All of the code necessary to run these algorithms, and apply them to the training data, is available on my researchgate homepage. [link] [comments]  |
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