A fairly common sub-problem in many machine learning and data science scenarios is the need to compute the similarity (or difference or distance) between two datasets. For example, if you select a ...

Researchers from Imperial and its spinout company SOLVE Chemistry have presented a chemical dataset at the prestigious AI conference NeurIPS that could help accelerate the use of machine learning to ...

Researchers have applied the tools of neuroscience to study when and how an artificial neural network can overcome bias in a dataset. They found that data diversity, not dataset size, is key and that ...

MIT researchers have developed a technique to identify and remove specific data points in training datasets that disproportionately contribute to a model's errors on minority subgroups. This approach ...

Machine learning is a rapidly growing field with endless potential applications. In the next few years, we will see machine learning transform many industries, including manufacturing, retail and ...

At first thought, computing the similarity/distance between two datasets sounds easy, but in fact the problem is extremely difficult, explains Dr. James McCaffrey of Microsoft Research. A fairly ...