Kernel methods form a foundational framework in statistical learning theory, enabling algorithms to operate in implicitly defined high-dimensional feature spaces without ever computing feature vectors ...

Are two sets of data genuinely different, or is it because of randomness? This question, known as the two-sample testing problem, becomes notoriously difficult in modern datasets, because they are ...