In label-noise learning, the noise transition matrix reveals how an instance transitions from its clean label to its noisy label. Accurately estimating an instance's noise transition matrix is crucial for estimating its clean label.

The fundamental problem of non-parametric two-sample testing consists in detecting the difference between any two distributions having access only to samples from these.

The joint decisions of the agents influence both individual rewards and the transition of the environment. MARL in general is occupied with leading the multi-agent system to a favorable outcome. Through the lens of game theory, the notion of a "favorable outcome" is formally defined through concepts like a Nash