Impact Statement: Partial label learning (PLL) is important in some applications when there exist some instances with a set of candidate labels. Different from the existing works, this paper considers ...

Abstract: At present, Symmetric Positive Definite (SPD) matrix data is the most common non-Euclidean data in machine learning. Because SPD data don’t form a linear space, most machine learning ...

You can use ML-Annotate to label text data for machine learning purposes. ML-Annotate supports binary, multi-label and multi-class labeling. Then you will have access to the application shell. Here's ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

Additionally, trials are expensive and might expose patients to unproven therapies. Alternatives to overcome these issues using virtual patient data—namely, digital twins, synthetic patient data, and ...