To improve the accuracy of recommendation scoring, this article proposes a score prediction algorithm that combines deep learning and matrix factorization. To address the problem of sparse scoring ...

Deep learning has been highly successful in recent years and has led to dramatic improvements in multiple domains. Deep-learning algorithms often generalize ... and there are certainly important ...

To solve this problem, a new transfer learning method, namely Wasserstein distance transfer learning algorithm based on matrix-norm regularization (MRWDTL), is proposed. To satisfy the Lipschitz ...

They all rely on matrix multiplication for accurate calculations. DeepMind, an artificial intelligence company, recently developed a faster algorithm to conduct matrix multiplications based on deep ..

An application using deep learning applied color ... computing required to run the matrix-based logic that characterizes machine-learning algorithms, Oppenheimer said. If an algorithm is open ...

Learn More Can artificial intelligence (AI) create its own algorithms to speed up matrix multiplication, one of machine learning’s ... “This gives us two very important results: One is that ...

Data analytics often rely on machine learning (ML) algorithms. Among ML algorithms, deep convolutional neural networks (DNNs) offer state-of-the-art accuracies for important image classification ...