Lasso performance, with the added benefit of providing multiple solutions.

This paper studies the problem of entropy identity testing: given sample access to a distribution p and a fully described distribution q (both discrete distributions over a domain of size k), and the promise that either p = q or |H (p) H (q)| ε, where H () denotes the Shannon entropy, a tester needs to distinguish between the two cases with high probability.

SRNNs are able to automatically identify discrete states with distinct nonlinear neural dynamics.