The observed values of the dependent variable, z, can be related to the independent variables, through, where ε is a noise term, which is here assumed to be independent and identically distributed according to a Gaussian distribution,.
Then the source generates independent and identically distributed according to distribution.
Relay node generates independent and identically distributed according to distribution and labels them, and for each generates 's, each with probability.
In BM, each jump is independent and identically distributed according to a normal distribution with variance proportional to the time between observations.
To simplify the problem, we assume that the inputs of the users are independently and identically distributed according to some random distribution ({mathcal {X}}).
Each node in the network may fail or not and failures are independently and identically distributed according to the Bernoulli distribution.
Most of the research in online learning is focused either on the problem of adversarial classification (i.e., both inputs and labels are arbitrarily chosen by an adversary) or on the traditional supervised learning problem in which samples are independent and identically distributed according to a stationary probability distribution.
The bivariate hazard model is λ T,ijk (t ; x ijk ) = λ T0 (t ) exp (x ijk β Ti + e Tij ) and λ D,ijk (d ; x ijk ) = λ D0 (d ) exp (x ijk β Di + e Dij ) where the [eTij eDij]'s are independent and identically distributed according to a bivariate normal distribution with null mean vector and positive-definite variance matrix.
The interruptions, from the LP packets point of view, are identically distributed due to the exponential LP service time distribution.
Under the assumption that the random components are independently and identically distributed according to a type I extreme-value distribution, the probability of choosing destination d over the others is the following: Pr x id β + ε id ≥ x ik β + ε ik for all k ≠ d = e x id β ∑ k = 1 D e x id β = P id ( x | β ).
