semimetrics

In real-world benchmarks on high-dimensional text and image data, linear-time tests using the proposed semimetrics achieve comparable performance to the state-of-the-art quadratic-time maximum mean discrepancy test, while returning human-interpretable features that explain the test results..

2016, Wittawat Jitkrittum, Zoltan Szabo, Kacper Chwialkowski, Arthur Gretton, “Interpretable Distribution Features with Maximum Testing Power”, in arXiv