ABSTRACT: A new nano-based architectural design of multiple-stream convolutional homeomorphic error-control coding will be conducted, and a corresponding hierarchical implementation of important class ...

An artificial-intelligence algorithm that discovers its own way to learn achieves state-of-the-art performance, including on some tasks it had never encountered before. Joel Lehman is at Lila Sciences ...

Modern C++17 Hidden Markov Model library with smart pointer memory management, comprehensive training algorithms, and critical bug fixes. Features Viterbi training, multiple probability distributions, ...

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...

Powerful and practical machine learning tools for machine vision applications are already available to everyone, even if you’re not a data scientist. It might come as a bit of a surprise, but machine ...

The emergence of using Machine Learning Techniques in software testing started in the 2000s with the rise of Model-Based Testing and early bug prediction models trained on historical defect data. It ...

Background: Fertility preferences refer to the number of children an individual would like to have, regardless of any obstacles that may stand in the way of fulfilling their aspirations. Despite the ...

The year 2024 is the time when most manual things are being automated with the assistance of Machine Learning algorithms. You’d be surprised at the growing number of ML algorithms that help play chess ...

When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...